2003 - 08 - 24 咸阳市大暴雨过程分析

利用高空、地面天气图、红外云图、多普勒雷达图等资料对临汾市2004年6月16日局地降雹的天气背景、形势演变、层结稳定度、云图和雷达回波等变化特征进行了综合分析，结合以往冰雹预报经验对新一代雷达的探测能力进行了初步检验。分析发现，这次降雹过程属典型的西北冷涡影响型，此类型降雹相对于西北气流型和西风槽型降雹具有其自身特征；从多普勒速度图上，可分析出降雹过程中飑线前后较明显的中尺度天气系统。     

近50 a青藏高原地面气温序列的重建

利用NCEP／NCAR500hPa高空再分析资料插补得到青藏高原1950—2000年50个海拔在3000m以上台站500hPa完整可靠的月平均温度序列。基于青藏高原地面气温和其上空500hPa温度有着密切关系，设计了这50个台站地面月平均温度序列的回归方案，用回归估计值将近50a各台站的现有月平均气温记录进行补齐、延长，得到重建的高原台站完整连续的地面月平均气温资料，并对回归效果进行独立样本实验。重建的青藏高原地面气温资料能够真实地反应高原实际气温的变化特征。     

水流冲击管道内滞留气团的刚性数学模型

通过数学分析证明,在不计局部水头损失时,目前常用的几种简化刚性数学模型的最大气压计算结果相等,并与管道内初始充水段长度无关。但算例表明,对于初始充水段较短或滞留气团体积很小情况,这些简化模型的计算误差将达到不容忽视的程度,甚至导出错误结论。笔者导出的完整刚性数学模型,弥补了简化模型的不足,同时指出了刚性模型的理论缺陷和适用条件。     

广东花岗岩类温泉水-汽转化过程中氡浓度的变化及其危害

广东省是我国温泉出露最多的省份之一。在温泉附近建立温泉宾馆,是利用温泉资源大力发展本地旅游业的有效途径之一。本文利用新型NR 667A连续测氡仪测量了广东省4处温泉宾馆室内外空气中氡浓度以及室内温泉水氡浓度。温泉水氡浓度变化范围为53 4～292 5Bq L,室外氡浓度范围是17～48Bq m3,而客房内平均氡浓度水平比没有用温泉水时高出10 9%～813%,浴室内氡浓度比没有用温泉水洗浴时高出13 8%～516%。在宾馆室内使用温泉水有较高的氡转换系数。某些宾馆室内氡浓度超标,可能对宾馆工作人员造成潜在健康危害,应采取一些管理措施或技术手段降低其暴露时间或程度。     

利用遥感综合分析西风引导气流与地形对沙尘运移路径的影响

沙尘暴的发生受大气环流、地表状况、降雨的影响，还受到局部地区地形的影响。一次规模较大的沙尘暴过程，沙尘可以从蒙古国和我国西部沙源地输送到我国东部、韩国、日本乃至夏威夷、美国西海岸。中日亚洲沙尘暴ADEC项目对亚洲沙尘暴的起沙、传输和降落的运行机制已经作了深入的研究，并建立了亚洲沙尘暴的数值模拟系统。本文以影响北京地区的沙尘暴事件为例，利用遥感技术，综合DEM地形数据和地面实测数据分析西风引导气流和地形对沙尘运移路径影响，将MODIs影像数据和DEM地形数据以及地面观测站点实测数据相结合，进行综合分析，结果表明在一次沙尘暴过程中，沙尘在运移过程中的运移路径明显地受到西风引导气流、沙尘粒子自然沉降规律以及局部地形的影响，要预防(减少)北京地区的沙尘暴仅仅作好北京地区的生态环境建设是不够的，加强北京周边地区，尤其是张家口地区、官厅水库库区及库区周围地区的生态环境建设尤为重要。     

沙尘天气等对西安市空气污染影响的研究

通过对西安市1981—2000年TSP、SO2和NOx年平均浓度资料,1998—2000年周报和日报环境监测资料以及相应的地面、高空常规气象观测资料的统计分析,研究了该市空气污染的时间变化特点以及沙尘天气等几种气象条件对其浓度变化的影响。结果表明:(1)颗粒污染物(TSP和PM10)是西安市的首要污染物,其次是SO2。1981—2000年期间,TSP年平均浓度降低了75%,SO2年平均浓度降低了77%,NOx年平均浓度总体上变化不大;这三种污染物月平均浓度的年变化都呈单周期型,冬季1月份最高,夏季最低(TSP是7月份最低,SO2和NOx是8月份最低)。(2)2001年春季3～4月份沙尘天气的频繁发生,使西安市空气污染日出现全年的第二个多发期(23d·月-1),这有别于正常年份仅在冬季1月份出现一个浓度峰值的特点;强沙尘暴天气过程会使西安市PM10浓度在非常短的时间内提高3倍左右,造成严重的颗粒物污染。(3)西安市冬半年出现轻度污染以上级别的几率明显大于夏半年。影响西安市的地面天气系统可归纳为12类,当受不同天气系统控制时,其污染状况会有较大差异。(4)西安市一年四季都有逆温存在,100m平均逆温强度为0.90℃;全年以低层逆温出现日数最多,但冬季贴地逆温出现日数最多,厚度最厚,强度最大,是造成西安市冬季空气污染严重的最重要气象因素之一。(5)西安     

西安市冬季冷暖的历史演变对采暖的影响

本文针对CAPPS2.0系统在业务化自动运行过程中的一些问题,提供了一套具体可行的解决方案,实现了CAPPS系统的全自动运行,具有很高的实用价值。     

侯马市酸雨概况及其气象条件分析

通过对侯马近14a酸雨观测资料分析,发现侯马出现酸雨的概率较大,强度较强,时间变化特征明显,与气象条件关系密切。     

Mesoscale Diagnosis of a Torrential Rainfall Caused by a Tropical Depression

On August 5, 2001, Shanghai was struck by a torrential rainfall due to the passage of a tropical depression (TD). The rainfall intensity has been the strongest in recent 50 years. In this paper, a set of mesoscale re-analyses data and the planetary boundary layer observation from a wind profiler are used to understand the possible mechanism of such a heavy rain. Results show that the outburst of a southerly jet in the lower atmosphere triggered the explosive development of cyclonically vertical vorticity in the region with steep potential temperature surfaces in front of the TD; while the cyclonic vorticity increased notably at higher levels due to the small atmospheric vertical stability of westerly currents in the vicinity of Shanghai. The simultaneous sharp development of cyclonic vorticity at different levels should be the main cause for the torrential rainfall.     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".