国土资源部关于印发《开采总量控制矿种指标管理暂行办法》的通知

国土资发〔2012〕44号各省、自治区、直辖市国土资源主管部门,新疆生产建设兵团国土资源局:为加强国家实行开采总量控制矿种指标管理,加强优势矿产资源开发的总量控制,防止过度开采,确保开采总量控制指标的严肃性,国土资源部研究制定了《开采总量控制矿种指标管理暂行办法》,现印发给你们,请遵照执行。     

精细化监测资料在山西暴雨预报模型改进中的应用

利用近3年5—9月山西63个GPS/MET临测站反演的逐时气柱水汽总量空间分布图与对应的459天气象观测资料、12个暴雨日的暴雨落区以及对应的流型配置图,对比分析发现:(1)当气柱水汽总量空间分布的水平梯度在25～40 mm/l经(纬)度时,未来12～36小时,在水平梯度的大值区及其南北(东西)0.5～1.0个经(纬)度的范围内,暴雨及其以上天气出现的概率达100%,当气柱水汽总量空间分布的水平梯度≥40 mm/l经(纬)度时,在水平梯度的大值区及其南北(东西)0.5个经(纬)度的范围内出现大暴雨的慨率为63.6%;(2)暴雨落区在气柱水汽总量空间分布图中水汽含量水平梯度大值区及其以北(西)还是以南(东)0.5～1.0)个经(纬)度的范围出现,不同的流型配置会出现不同的结果。应用逐时GPS/MET资料和逐时自动气象站极大风速风场资料,依据暴雨出现在气柱水汽总量空间分布图中水汽含量水平梯度大值区的不同位置,建立不同流型配置下的多种暴雨概念模型;采用轮廓识别技术在C/S架构下,对12～36小时暴雨落区预报模型进行改进并实现了自动化运行,2011年进行准业务使用证明效果良好。     

地基GPS水汽总量在人工增雨中的应用

利用成都市地基GPS综合应用网的观测数据,反演出大气水汽总量,并结合多普勒天气雷达探测的垂直积分液态水含量(VIL),分析了这两种新型大气水汽探测资料在人工影响天气作业中的变化特征,初步得出了GPS大气水汽总量(GPS PWV)与人影作业前后降雨量的关系。研究表明:GPS PWV与人工增雨过程有较好的对应关系,人影作业后1～3h伴随小时雨量的增大GPS PWV有下降,体现了催化剂将空中部分冰面过饱和水汽凝华核化转化为降水过程。GPS反演的水汽资料结合新一代多普勒天气雷达探测的液态水资料在指导人工影响天气作业和短临天气预报方面具有良好的应用前景。     

Sensitivity of Tropical Cyclone Precipitation to Atmospheric Moisture Content： Case Study of Bilis （2006）

In this article, the authors used the Weather Research and Forecast model to investigate the sensitivity of tropical cyclone Bilis' total precipitation to ambient water vapor content. The tropical cycl...     

平流层爆发性增温过程中臭氧的垂直分布特征

利用ECMWF资料分析了平流层爆发性增温 (SSW) 过程中臭氧体积混合比的垂直分布的变化, 结果表明: 平流层爆发性增温过程中臭氧体积混合比增大, 而其极大值大多数形成在增温盛期。同时臭氧体积混合比的高值区在爆发性增温过程中随高度发生一定的变化, 据此对其变化分为两类: (1) 下传型: 在增温初期臭氧体积混合的高值区随高度下传至一定高度, 在增温盛期形成极大值然后随高度抬升到大致增温前的高度。 (2) 增厚型: 在增温过程中臭氧体积混合比的高值区厚度增加, 同时附近区域的臭氧体积混合比也增大, 而且在增温前臭氧体积混合比高值区在高度上没有多大变化, 增温开始后有所抬升。平流层爆发性增温过程中臭氧高值区随高度变化的这两种类型, 是由于平流层爆发性增温期间剩余环流对臭氧输送的结果。臭氧变化的下传型是由于在爆发性增温前剩余环流存在着中纬度向极地的明显输送, 并且伴随着极地强烈的下沉运动, 这就使得中纬度输送来的臭氧向下输送, 因此出现了臭氧高值区的下传; 而臭氧变化的增厚型是由于在爆发性增温期间剩余环流不但有中纬度向极地的输送, 而且在极地附近5 hPa高度处出现了上下两支输送气流, 向上的输送气流使中纬度输送来的臭氧向上输送, 而向下的输送气流使中纬度输送来的臭氧向下输送, 进而使增温期间极地附近的臭氧的高值区增厚。同时分析还表明: 平流层爆发性增温过程中中纬度臭氧体积混合比减少。     

利用卫星资料分析我国北方东西部臭氧分布差异

利用SAGE Ⅱ和HALOE臭氧垂直分布资料和TOMS臭氧总量资料, 研究我国北方(45°~55°N和35°~45°N范围), 东部(105°~135°E) 和西部(75°~105°E) 大气臭氧总量和垂直分布特征和差异。结果表明:我国北方东部冬季、春季和秋季臭氧总量明显大于西部, 主要表现在平流层臭氧极大值附近及其以下高度臭氧含量东部比西部明显偏大, 这种差异在冬、春季尤为明显; 随着纬度的降低, 冬季和秋季臭氧总量东、西部差异减小, 但春季臭氧总量东、西部差异没有明显改变; 夏季, 在45°~55°N范围, 东、西部臭氧分布没有明显差异, 但在35°~45°N范围, 臭氧分布东、西部差异较明显, 臭氧总量东、西部差异达到20.6 DU, 16 km以下臭氧柱总量东、西部差异达到12.8 DU。该文还对导致我国东、西部臭氧分布差异的原因进行了分析。     

Vertical Observations and Analysis of PM2.5, O3, and NOx at Beijing and Tianjin from Towers during Summer and Autumn 2006

During the period between 18 August and 22 September 2006, an ultraviolet photometric O3 analyzer, a NO-NO2-NOx chemiluminescence analyzer, and a quartz micro-oscillating-scale particle concentration analyzer were simultaneously used for monitoring at three different heights each at Beijing (325-m tower) and Tianjin (255-m tower). These towers belong to the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences (CAS) and to the Tianjin Municipal Meteorological Bureau, respectively. These measurements were used to continuously measure the atmospheric O3 and NOx volume-by-volume concentrations and the PM2.5 mass concentration within a vertical gradient. When combined with meteorological data and information on the variation of vertical characteristics of the various atmospheric pollutants in the two cities, analysis shows that these two cities were seriously polluted by both PM2.5 and O3 during summer and autumn. The highest daily-average concentrations of PM2.5 near the ground in Beijing and Tianjin reached 183 μg m-3 and 165 μg m-3, respectively, while the O3 concentrations reached 52 ppb and 77 ppb, and NOx concentrations reached 48 ppb and 62 ppb for these two cities, respectively. The variations in the daily-average concentrations of PM2.5 between Beijing and Tianjin were demonstrated to be consistent over time. The concentrations of PM2.5 measured in Beijing were found to be higher than those in Tianjin. However, the overall O3 concentrations near the ground in Tianjin were higher than in Beijing. NOx concentrations in Tianjin were consistently lower than in Beijing. It was also found that PM2.5 pollution in Beijings atmosphere may also be affected by the pollutants originating in and delivered from Tianjin, and that Ti     

Tropospheric NO2 Columns over Northeastern North America： Comparison of CMAQ Model Simulations with GOME Satellite Measurements

We present comparisons of the NO2 regional Chemical Transport Model （CTM） simulations over North-eastern North America during the time period from May to September, 1998 with hourly surface NO2 observations and the NO2 columns retrieved from the GOME （Global Ozone Monitoring Experiment） satellite instrument. The model calculations were performed using the Mesoscale Meteorological Model 5 （MM5）, Sparse Matrix Operator Kernal Emissions （SMOKE）, and Community Multiscale Air Quality （CMAQ） modeling systems, using the emission data from the National Emissions Inventory （NEI） databases of 1996 （U.S.） and 1995 （Canada）. The major objectives were to assess the performance of the CMAQ model and the accuracy of the emissions inventories as they affected the simulations of this important short-lived atmospheric species. The modeled （NcMAQ） and measured （NGOME） NO2 column amounts, as well as their temporal variations, agreed reasonably well. The absolute differences （NcMAQ-NGOME） across the domain were between ±3.0×10^15 molecules cm^-2, but they were less than ±1.0×10^15 molecules cm^-2 over the majority （80%） of the domain studied. The overall correlation coefficient between the measurements and the simulations was 0.75. The differences were mainly ascribed to a combination of inaccurate emission data for the CTM and the uncertainties in the GOME retrievals. Of these, the former were the more easily identifiable.     

蒙特卡罗不确定性分析在O3模拟中的初步应用

利用蒙特卡罗不确定性分析方法,分析了嵌套网格空气质量模式系统(NAQPMS/IAP)中154个模式输入变量不确定性对臭氧模拟的影响,量化了模式在北京奥运会期间臭氧模拟的不确定性,并确定出了主要不确定性因子。结果表明:(1)在奥运会期间(2008年8月8日～2008年8月24日),北京城区臭氧模拟的平均不确定性为19ppb,不确定性存在明显的日变化特征,白天不确定性大,夜间不确定性小。(2)在白天,北京城区近地层臭氧模拟最重要的不确定性来源是局地前体物排放,其次是NO2光解系数、风向、北京周边前体物排放和垂直扩散系数。另外,地面约150m以上,对臭氧模拟影响最大的不确定性因子是风向和北京周边前体物排放;夜间,北京城区近地层臭氧模拟的最大不确定性来源是局地NOx排放和垂直扩散系数。     

BREWER观测数据报表的自动形成

1引言BREWER是龙凤山站测量臭氧总量和紫外线辐射的主要仪器,它的数据输出主要有两种方式:一种是ASSIC码的文本文件,文件比较长,其中的数据代表的含义不容易记,所以使用不方便;另一种方式是打印文件,手动计算和添加到月报表中,最后输入计算机中再