上海气象梯度塔观测数据质量控制与运行效能评估
Quality Control and Operation Evaluation of Meteorological Gradient Towers in Shanghai
孙娟 1胡平 2谢媛 2黄国权2
作者信息
- 1. 上海市气象信息与技术支持中心,上海200030;南京信息工程大学,江苏南京210044
- 2. 上海市气象信息与技术支持中心,上海200030
- 折叠
摘要
[目的]评估上海气象梯度塔2010～2013年观测数据质量及设备运行效能.[方法]基于上海地区现有的9座气象梯度观测塔2010～2013年的分钟级观测数据,针对气温、相对湿度、水平风向和水平风速等观测要素,根据梯度塔立体垂直的观测特点,建立了梯度观测数据质量控制模型并对梯度数据进行了综合质量控制；从数据获取率、数据疑误率、数据有效性等方面对梯度数据进行了统计与评估.[结果]2010年度的数据接收、存储最为完整,2011年度最差；气温、风速的观测数据异常情况较少,湿度和风向数据的异常较多；极值控制检查出了较多的气温异常情况；分钟连续性和小时连续性可以检查出气温和相对湿度的异常跳变；僵值检查可在每一个要素的质量控制中发挥出重要的作用.[结论]该研究可为上海地区近地层大气的风温结构特征研究提供更加准确、客观的梯度观测数据.
Abstract
[Objective] The aim was to evaluate observational data quality and equipment operation performance in Shanghai meteorological gra dient towers during 2010 - 2013. [ Method ] Based on minute observation data of 9 meteorological gradient towers in Shanghai during 2010 - 2013,aiming at observational elements such as temperature,relative humidity,horizontal wind direction and wind speed,according to vertical observation features of gradient towers,data quality control model was established,comprehensive quality control of gradient data was conducted;data was evaluated from aspects of acquisition rate. false rate and validity. [ Result ] Ihe results showed that data receiving, storage in 2010 is most complete, the worst in 2011 ; air temperature, wind speed of the observed data anomalies are less , the humidity and wind direction data is more abnormal; extreme control check out a lot of temperature anomalies ; minute and hour continuity can check temperature and relative humidity in Lhe abnormal jump; dead value inspection plays an important role in quality control of each element. [ Conclusion ] The study can provide more accurate and objective gradient observation data for research on the structure characteristics of air temperature in the near surface layer in Shanghai.
关键词
气象梯度塔/观测数据/质量控制/运行评估Key words
Meteorological gradient observation tower/Observation data/Quality control/Operation evaluation引用本文复制引用
基金项目
上海市气象局研究型项目(YJ201509)
江苏省普通高校研究生科研创新计划(CXLX13_495)
出版年
2016
国家科技期刊平台
NSTL
维普
万方数据