渤海海域海上观测站逐时气温和气压的质量控制分析-海洋预报

渤海海域海上观测站逐时气温和气压的质量控制分析

单位：1. 天津市气象信息中心, 天津 300074;
2. 广东省韶关市气象局, 广东韶关 512026

分类号：P732.1

出版年·卷·期（页码）：2023·40·第三期（97-103）

摘要：

为有效提高海洋观测质量，选取渤海海域2019年19个海上自动气象观测站的逐时气温和气压，利用界限值检查、气候变化范围检查、内部一致性检查、时间一致性检查和空间一致性检查方法，对数据进行质量控制分析。结果表明：逐时气压的数据质量优于逐时气温，所有站点逐时气压数据的可用率均在99%以上，而3个站点的逐时气温数据质量较差，可用率分别为88.9%、91.3%和92.3%，错误主要表现为连续一段时间内气温出现异常。经过质量控制剔除错误值后，站点观测资料数据与ERA5再分析资料的相关系数均有所提升；经质量控制后的观测气温和气压的均方根误差减小，相关系数增大。因此，经过上述质量控制方法可有效剔除不合理数值，避免其由于直接使用带来的偏差。

To effectively advance the quality of marine observation data, quality control analysis are applied to the hourly air temperature and pressure observations from 19 marine stations in the Bohai Sea in 2019. The quality control methods include maximum-minimum checking, climatological changing range checking, internal consistency checking, temporal consistency checking and spatial consistency checking. The results demonstrate that: the data quality of the observed pressure is better than that of the observed temperature, data availability rate of hourly pressure is above 99% for all the stations, however data availability rate of hourly temperature at 3 of the stations are relative low, with values of 88.9%、 91.3% and 92.3%, and the abnormal temperature data appears in a continuous period. Comparison between the hourly observations and ERA5 reanalysis data shows that, after applying the quality control analysis, the root mean square error between the observations and reanalysis data has decreased, and their correlation coefficient has increased. Therefore the quality control methods can effectively eliminate the unreasonable value of data.

参考文献：

[1] 李帅, 郭俊如, 姜晓轶, 等. 海洋水文气象多时空尺度资料来源分析[J]. 海洋通报, 2020, 39(1):24-39. LI S, GUO J R, JIANG X Y, et al. Sources and analysis of multitemporal-spatial scale marine hydrometeorology data[J]. Marine Science Bulletin, 2020, 39(1):24-39.
[2] 王亚男, 刘一玮, 易笑园. 渤海西部雷雨大风统计特征及对流参数指标分析[J]. 气象, 2020, 46(3):325-335. WANG Y N, LIU Y W, YI X Y. Statistical characteristics and convection indexes of thunderstorm and gale over western Bohai Sea[J]. Meteorological Monthly, 2020, 46(3):325-335.
[3] 司鹏, 朱男男, 苏杭, 等. 绥中36号海上石油平台站业务化评估及其风速资料的质量检测[J]. 海洋预报, 2019, 36(1):27-36. SI P, ZHU N N, SU H, et al. Operational evaluation and wind speed data quality check of a station on Suizhong 36 offshore oil platform[J]. Marine Forecasts, 2019, 36(1):27-36.
[4] 司鹏, 梁冬坡, 朱男男, 等. 黄渤海海域16个石油平台站风速资料的初步质量检测[J]. 海洋预报, 2020, 37(1):43-49. SI P, LIANG D P, ZHU N N, et al. Preliminary quality verification of wind speed data observed by 16 oil platform monitoring stations in the Yellow Sea and Bohai Sea[J]. Marine Forecasts, 2020, 37(1):43-49.
[5] 杨扬, 苗庆生, 韦广昊, 等. 海洋站观测资料的质量控制方法及其应用[J]. 海洋开发与管理, 2017(10):109-113. YANG Y, MIAO Q S, WEI G H, et al. Quality control methods and application for the oceanic station observed data in the delayed mode[J]. Ocean Development and Management, 2017(10):109-113.
[6] 刘玉龙, 王国松, 侯敏, 等. 基于深度学习的海温观测数据质量控制应用研究[J]. 海洋通报, 2021, 40(3):283-291. LIU Y L, WANG G S, HOU M, et al. Quality control of sea temperature observation data using deep learning neural networks[J]. Marine Science Bulletin, 2021, 40(3):283-291.
[7] YANG H, GAO Q Q, JI H F, et al. Sea surface temperature data from coastal observation stations:quality control and semidiurnal characteristics[J]. Acta Oceanologica Sinica, 2019, 38(11):31-39.
[8] 中国气象局. QX/T 118-2020气象观测资料质量控制地面[S]. 北京:气象出版社, 2020:1-8. China Meteorological Administration. QX/T 118-2020 Quality control of meteorological observation data-surface[S]. Beijing:China Meteorological Press, 2020:1-8.
[9] 王海军, 杨志彪, 杨代才, 等. 自动气象站实时资料自动质量控制方法及其应用[J]. 气象, 2007, 33(10):102-109. WANG H J, YANG Z B, YANG D C, et al. The method and application of automatic quality control for real time data from automatic weather stations[J]. Meteorological Monthly, 2007, 33(10):102-109.
[10] 任芝花, 张志富, 孙超, 等. 全国自动气象站实时观测资料三级质量控制系统研制[J]. 气象, 2015, 41(10):1268-1277. REN Z H, ZHANG Z F, SUN C, et al. Development of three-step quality control system of real-time observation data from AWS in China[J]. Meteorological Monthly, 2015, 41(10):1268-1277.
[11] QIAN C C, LIU A C, HUANG R, et al. Quality control of marine big data-a case study of real-time observation station data in Qingdao[J]. Journal of Oceanology and Limnology, 2019, 37(6):1983-1993.
[12] 江益, 王立俊, 羊清雯, 等. 南海区域站气象资料质量控制方法改进[J]. 气象科技, 2018, 46(3):474-478. JIANG Y, WANG L J, YANG Q W, et al. Improvement of quality control method for real time meteorological data from regional automatic stations on South China Sea[J]. Meteorological Science and Technology, 2018, 46(3):474-478.
[13] 郭春迓, 李天然, 胡东明, 等. 南海北部测站风速质量的控制方法[J]. 广东气象, 2016, 38(1):44-48. GUO C Y, LI T R, HU D M, et al. Quality Control methods of wind speed at the northern South China Sea station. Guangdong Meteorology, 2016, 38(1):44-48.
[14] DECKER M, BRUNKE M A, WANG Z, et al. Evaluation of the reanalysis products from GSFC, NCEP, and ECMWF using flux tower observations[J]. Journal of Climate, 2011, 25(6):1916-1944.
[15] 申华羽, 吕劲文, 涂小萍, 等. ERA-Interim和NCEP/NCAR再分析资料在我国东南近海适用性分析[J]. 海洋预报, 2019, 36(2):9-20. SHEN H Y, LYU J W, TU X P, et al. The applicability of ERAInterim and NCEP/NCAR reanalysis datasets in the adjacent waters of the southeast China Sea[J]. Marine Forecasts, 2019, 36(2):9-20.
[16] 谭海燕, 邵珠晓, 梁丙臣, 等. ERA5风场与NCEP风场在黄海、东海波浪模拟的适用性对比研究[J]. 海洋通报, 2021, 40(5):524-540. TAN H Y, SHAO Z X, LIANG B C, et al. A comparative study on the applicability of ERA5 wind and NCEP wind for wave simulation in the Huanghai Sea and East China Sea[J]. Marine Science Bulletin, 2021, 40(5):524-540.
[17] KEARNS E, WOODY C, BUSHNELL M. QARTOD-I Report. First workshop report on the quality assurance of real-time ocean data[R]. Boston:National Data Buoy Center, 2004.

服务与反馈：

【文章下载】【发表评论】【查看评论】【加入收藏】