Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/joc.5037 |
Identifying, attributing, and overcoming common data quality issues of manned station observations | |
Hunziker, Stefan1,2; Gubler, Stefanie3; Calle, Juan4; Moreno, Isabel4; Andrade, Marcos4; Velarde, Fernando4; Ticona, Laura4; Carrasco, Gualberto5; Castellon, Yaruska5; Oria, Clara6; Croci-Maspoli, Mischa3; Konzelmann, Thomas3; Rohrer, Mario7; Bronnimann, Stefan1,2 | |
2017-09-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY |
ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2017 |
卷号 | 37期号:11 |
文章类型 | Article |
语种 | 英语 |
国家 | Switzerland; Bolivia; Peru |
英文摘要 | In situ climatological observations are essential for studies related to climate trends and extreme events. However, in many regions of the globe, observational records are affected by a large number of data quality issues. Assessing and controlling the quality of such datasets is an important, often overlooked aspect of climate research. Besides analysing the measurement data, metadata are important for a comprehensive data quality assessment. However, metadata are often missing, but may partly be reconstructed by suitable actions such as station inspections. This study identifies and attributes the most important common data quality issues in Bolivian and Peruvian temperature and precipitation datasets. The same or similar errors are found in many other predominantly manned station networks worldwide. A large fraction of these issues can be traced back to measurement errors by the observers. Therefore, the most effective way to prevent errors is to strengthen the training of observers and to establish a near real-time quality control (QC) procedure. Many common data quality issues are hardly detected by usual QC approaches. Data visualization, however, is an effective tool to identify and attribute those issues, and therefore enables data users to potentially correct errors and to decide which purposes are not affected by specific problems. The resulting increase in usable station records is particularly important in areas where station networks are sparse. In such networks, adequate selection and treatment of time series based on a comprehensive QC procedure may contribute to improving data homogeneity more than statistical data homogenization methods. |
英文关键词 | quality control error attribution station observations data rescue metadata data homogenization Bolivia Peru |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000409036800012 |
WOS关键词 | HISTORICAL CLIMATOLOGY NETWORK ; DAILY TEMPERATURE ; MICROCLIMATE EXPOSURES ; COOPERATIVE NETWORK ; PRECIPITATION DATA ; WEATHER STATIONS ; WEEKLY CYCLES ; DATA SET ; EXTREMES ; INDEXES |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/36691 |
专题 | 气候变化 |
作者单位 | 1.Univ Bern, Inst Geog, Hallerstr 12, CH-3012 Bern, Switzerland; 2.Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland; 3.Fed Off Meteorol & Climatol MeteoSwiss, Zurich, Switzerland; 4.Univ Mayor San Andres, Inst Invest Fis, Lab Fis Atmosfera, La Paz, Bolivia; 5.Serv Nacl Meteorol & Hidrol Bolivia SENAMHI, La Paz, Bolivia; 6.Serv Nacl Meteorol & Hidrol Peru SENAMHI, Lima, Peru; 7.Meteodat GmbH, Zurich, Switzerland |
推荐引用方式 GB/T 7714 | Hunziker, Stefan,Gubler, Stefanie,Calle, Juan,et al. Identifying, attributing, and overcoming common data quality issues of manned station observations[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2017,37(11). |
APA | Hunziker, Stefan.,Gubler, Stefanie.,Calle, Juan.,Moreno, Isabel.,Andrade, Marcos.,...&Bronnimann, Stefan.(2017).Identifying, attributing, and overcoming common data quality issues of manned station observations.INTERNATIONAL JOURNAL OF CLIMATOLOGY,37(11). |
MLA | Hunziker, Stefan,et al."Identifying, attributing, and overcoming common data quality issues of manned station observations".INTERNATIONAL JOURNAL OF CLIMATOLOGY 37.11(2017). |
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