陕西省2016年自动土壤水分数据质量分析

采用数据缺测检查、范围(极值)检查、数据时变检查、物理常数检查和僵尸数据检查等方法,对陕西2016年53套固定地段土壤水分观测10～30 cm土层的体积含水量数据进行质量控制和原因分析。结果表明:各站缺测率均小于0.5%,最大为0.33%,最小为0.03%;1 h缺测时长最多,占比为64.4%;通信问题是短时缺测主要原因。范围检查检出数据为0的异常记录131 h,主要由该层传感器故障或因连接线松动、脱落造成,没有检出小于0或大于55%的记录。时变检查10、20、30 cm土层分别检出异常记录41、22、26 h,其中,10 cm土层检出率最高;突变主要是由于传感器防护管周围土壤发生龟裂或下陷。物理常数检查有17站发生一层或多层数据异常,其中, 53735等站三个土层全部出现异常,而且异常记录较多,异常站点随土层加深而减少。僵尸检查没有发现异常。物理常数检查异常表明这些地方的土壤结构和生态功能可能正在发生变化,需要进一步加强监测。     

基于标准差分析法的X波段双偏振天气雷达资料质量评估

2015年9月,北京市气象局在北京地区架设4部X波段双线偏振天气雷达并开展了观测试验。本文利用其中3部雷达在2016年6月30日的观测数据,用标准差分布统计方法,对雷达的观测参量进行初步质量评估。结果表明:(1)3部雷达反射率标准差符合理论值的数据占总观测数据的73.5%~77.9%,反射率的数据波动基本符合理论分布;(2)3部雷达差分反射率标准差符合理论值的数据占总观测数据的68.4%~81.4%,其中房山雷达数据波动较大;(3)3部雷达互相关系数标准差符合理论值的数据占总观测数据的45.7%~63.5%,其中房山雷达数据波动最大,其他2部雷达都有同程度的数据波动;(4)3部雷达差分传播相位标准差符合理论值的数据占总观测数据的73.5%~83.9%,其中房山雷达数据波动相对较大,与雷达其他观测参量相比,差分传播相位的波动较小。     

NO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> change over China and its influences

A 3-D chemical transport model (OSLO CTM2) is used to investigate the impact of the increase of NOx emission over China. The model is capable to reproduce basically the seasonal variation of surface NOx and ozone over eastern China. NOx emission data and observations reveal that NOx over eastern China increases quite quickly with the economic development of China. Model results indicate that NOx concentration over eastern China increasingly rises with the increase of NOx emission over China, and accelerates to increase in winter. When the NOx emission increases from 1995 to its double, the ratio of NO2/NOx abruptly drops in winter over northern China. Ozone at the surface decreases in winter with the continual enhancement of the NOx level over eastern China, but increases over southern China in summertime. It is noticeable that peak ozone over northern China increases in summer although mean ozone changes little. In summer, ozone increases in the free troposphere dominantly below 500 hPa.Moreover, the increases of total ozone over eastern China are proportional to the increases of NOx emission.In a word, the model results suggest that the relationship between NOx and ozone at the surface would change with NOx increase.     

基于GIS的洪涝灾害遥感评估系统

利用NOAA／AVHRR气象卫星实时监洲到的洪涝灾害数据与GIS技术相结合，以地理信息系统软件AreView3．1为依托建立洪涝灾害遥感评估系统。系统可提供洪涝区域内居民区的受淹数据，并进行受淹区域的比例系数计算，提供水田、旱田、林地、灌丛、果树和草地等淹没面积的信息。     

自动气象站异常数据处理办法及思路

<正>1引言在气象观测中,自动气象站的维修、维护不到位或不标准都可能带来观测数据异常的情况。本文对自动气象站不同数据文件异常情况处理进行说明,为相关工作人员提供参考。     

A New Method for Calculating the Wind Speed Distribution of a Moving Tropical Cyclone

Based on gradient wind equations,including frictional force,and considering the effect of the movement of a tropical cyclone on wind speed,the Fujita Formula is improved and further simplified,and the numerical scheme for calculating the maximum wind speed radius and wind velocity distribution of a moving tropical cyclone is derived.In addition,the effect of frictional force on the internal structure of the tropical cyclone is discussed.By comparison with observational data,this numerical scheme demonstrate...     

Estimation of Land Surface Temperature over the Tibetan Plateau Using AVHRR and MODIS Data

Estimation of large-scale land surface temperature from satellite images is of great importance for the study of climate change. This is especially true for the most challenging areas, such as the Tibetan Plateau (TP). In this paper, two split window algorithms (SWAs), one for the NOAA’s Advanced Very High Resolu-tion Radiometer (AVHRR), and the other for the Moderate Resolution Imaging Spectroradiometer (MODIS), were applied to retrieve land surface temperature (LST) over the TP simultaneously. AVHRR and M...     

Visual C#批量处理气候观测资料方法

气象观测数据是认识和预测天气变化、探索气候演变规律、进行科学研究和提供气象服务的基础。在气候资料服务中,需从原始观测数据中,提取某一时间范围内所需气象要素,并经过计算、筛选及格式化,输出新文件以方便用户使用。Microsoft的．NET开发工具C#是微软公司推出的一种语法简洁、类型安全的面向对象的编程语言,     

Excel在地面气象观测数据整编中的应用

运用Excel具有的数据输入和编辑、公式与函数,对地面气象测报业务软件OSSMO 2004/ReportFile/AIIiii-YYYYMM.TXT中的观测数据进行归类整理。     

Comparisons of Simulations of Soil Moisture Variations in the Yellow River Basin Driven by Various Atmospheric Forcing Data Sets

Based on station observations, The European Centre for Medium-Range Weather Forecasts reanalysis (ERA40), the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and Princeton University's global meteorological forcing data set (Princeton), four atmospheric forcing fields were constructed for use in driving the Community Land Model version 3.5 (CLM3.5). Simulated soil moisture content throughout the period 1951-2000 in the Yellow River basin was vali...