Dust-storm is a kind of severe weather, which has comprehensive and significant impacts on socioeconomic development and people’s livelihood. Enhancing the abilities of dust-storm monitoring, predicting and service w...Dust-storm is a kind of severe weather, which has comprehensive and significant impacts on socioeconomic development and people’s livelihood. Enhancing the abilities of dust-storm monitoring, predicting and service will be of great benefit and the important significance to China and its people. At present, the comprehensive operation on dust-storm monitoring, predicting and service is still in a preliminary phase, the abilities of operation can’t meet the needs of implementing the real-time and quantitative monitoring and providing the efficient service. The implementation of the project of dust-storm monitoring, predicting and service system will greatly improve the service ability and level for the sustainable development and make a greater contribution to build the better-off society. The first phase project mainly involves monitoring subsystem, predicting, warning and service subsystem; communications and transmission subsystem, etc. In the first phase construction a series of major measures should be taken to address project overall benefits, such as making better use of current monitoring resource, taking into account the standards of data format and project integrative and extensive abilities and so on.展开更多
It is difficult to estimate the effects of vegetation on dust-storm intensity （DSI） since land surface data are often recorded aerially while DSI is recorded as point data by weather stations. Based on combining bot...It is difficult to estimate the effects of vegetation on dust-storm intensity （DSI） since land surface data are often recorded aerially while DSI is recorded as point data by weather stations. Based on combining both types of data, this paper analyzed the relationship be- tween vegetation and DSI, using a panel data-analysis method that examined six years of data from 186 observation stations in China. The multiple regression results showed that the relationship between changes in vegetation and variance in DSI became weaker from the sub-humid temperate zone （SHTZ） to dry temperate zone （DTZ）, as the average normalized difference vegetation index decreased in the four zones in the study area. In the SHTZ and DTZ zones, the regression model could account for approximately 24.9% and 8.6% of the DSI variance, respectively. Lastly, this study provides some policy implications for combating dust storms.展开更多
针对2021年3月15日中国北方发生的沙尘暴事件,提出了一种基于大气可降水量差值的方法,旨在探究GNSS站点反演的大气可降水量与大气颗粒物浓度之间的相关性.选取了位于宁夏中卫(NXZW)、北京房山(BJFS)和吉林长春(CHAN)的3个GNSS站点及附...针对2021年3月15日中国北方发生的沙尘暴事件,提出了一种基于大气可降水量差值的方法,旨在探究GNSS站点反演的大气可降水量与大气颗粒物浓度之间的相关性.选取了位于宁夏中卫(NXZW)、北京房山(BJFS)和吉林长春(CHAN)的3个GNSS站点及附近的大气颗粒物浓度数据进行分析.结果显示,在非沙尘暴条件下,GNSS解算的大气可降水量(precipitable water vapor,PWV)精度表现良好,其与ERA5模型的PWV的差值均值和标准差均约在2 mm,证明了解算结果的可靠性.沙尘暴发生前,各站点PWV与大气颗粒物浓度的相关性均低于20%,表现出较弱的相关性.在沙尘暴期间,该相关性显著提高,尤其在BJFS和CHAN站点,PWV与大气颗粒物浓度的相关性超过60%.相位滞后消除后,NXZW站点的相关性更是达到70.25%.进一步分析还发现,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性也显著提高,其中BJFS和CHAN站点的相关性超过70%.综合分析表明,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性进一步增高,这表明大气颗粒物对PWV差值的贡献比对PWV本身的贡献显著增加,从而说明了PWV差值方法在大气颗粒物浓度监测方面的潜在应用价值.因此,本研究提供了一种新的研究思路和方法,为大气颗粒物浓度和气象条件之间复杂交互关系的进一步研究奠定了基础.展开更多
文摘Dust-storm is a kind of severe weather, which has comprehensive and significant impacts on socioeconomic development and people’s livelihood. Enhancing the abilities of dust-storm monitoring, predicting and service will be of great benefit and the important significance to China and its people. At present, the comprehensive operation on dust-storm monitoring, predicting and service is still in a preliminary phase, the abilities of operation can’t meet the needs of implementing the real-time and quantitative monitoring and providing the efficient service. The implementation of the project of dust-storm monitoring, predicting and service system will greatly improve the service ability and level for the sustainable development and make a greater contribution to build the better-off society. The first phase project mainly involves monitoring subsystem, predicting, warning and service subsystem; communications and transmission subsystem, etc. In the first phase construction a series of major measures should be taken to address project overall benefits, such as making better use of current monitoring resource, taking into account the standards of data format and project integrative and extensive abilities and so on.
基金National Natural Science Foundation of China,No.41271119,No.91325302No.41161140352National Basic Research Program of China,No.2015CB452705
文摘It is difficult to estimate the effects of vegetation on dust-storm intensity （DSI） since land surface data are often recorded aerially while DSI is recorded as point data by weather stations. Based on combining both types of data, this paper analyzed the relationship be- tween vegetation and DSI, using a panel data-analysis method that examined six years of data from 186 observation stations in China. The multiple regression results showed that the relationship between changes in vegetation and variance in DSI became weaker from the sub-humid temperate zone （SHTZ） to dry temperate zone （DTZ）, as the average normalized difference vegetation index decreased in the four zones in the study area. In the SHTZ and DTZ zones, the regression model could account for approximately 24.9% and 8.6% of the DSI variance, respectively. Lastly, this study provides some policy implications for combating dust storms.
文摘针对2021年3月15日中国北方发生的沙尘暴事件,提出了一种基于大气可降水量差值的方法,旨在探究GNSS站点反演的大气可降水量与大气颗粒物浓度之间的相关性.选取了位于宁夏中卫(NXZW)、北京房山(BJFS)和吉林长春(CHAN)的3个GNSS站点及附近的大气颗粒物浓度数据进行分析.结果显示,在非沙尘暴条件下,GNSS解算的大气可降水量(precipitable water vapor,PWV)精度表现良好,其与ERA5模型的PWV的差值均值和标准差均约在2 mm,证明了解算结果的可靠性.沙尘暴发生前,各站点PWV与大气颗粒物浓度的相关性均低于20%,表现出较弱的相关性.在沙尘暴期间,该相关性显著提高,尤其在BJFS和CHAN站点,PWV与大气颗粒物浓度的相关性超过60%.相位滞后消除后,NXZW站点的相关性更是达到70.25%.进一步分析还发现,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性也显著提高,其中BJFS和CHAN站点的相关性超过70%.综合分析表明,沙尘暴发生时,PWV差值与大气颗粒物浓度的相关性进一步增高,这表明大气颗粒物对PWV差值的贡献比对PWV本身的贡献显著增加,从而说明了PWV差值方法在大气颗粒物浓度监测方面的潜在应用价值.因此,本研究提供了一种新的研究思路和方法,为大气颗粒物浓度和气象条件之间复杂交互关系的进一步研究奠定了基础.
