Automatic processing of atmospheric CO2 and CH4 mole fractions at the ICOS Atmosphere Thematic Centre
| Autor: | Olivier Laurent, Amara Abbaris, Michel Ramonet, Lynn Hazan, Jérôme Tarniewicz |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Atmospheric Science
Data processing 010504 meteorology & atmospheric sciences Meteorology Traceability 010501 environmental sciences 01 natural sciences Atmosphere Thematic map 13. Climate action Greenhouse gas Outlier Calibration Environmental science Water vapor 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Atmospheric Measurement Techniques. 9:4719-4736 |
| ISSN: | 1867-8548 |
| Popis: | The Integrated Carbon Observation System Atmosphere Thematic Centre (ICOS ATC) automatically processes atmospheric greenhouse gases mole fractions of data coming from sites of the ICOS network. Daily transferred raw data files are automatically processed and archived. Data are stored in the ICOS atmospheric database, the backbone of the system, which has been developed with an emphasis on the traceability of the data processing. Many data products, updated daily, explore the data through different angles to support the quality control of the dataset performed by the principal operators in charge of the instruments. The automatic processing includes calibration and water vapor corrections as described in the paper. The mole fractions calculated in near-real time (NRT) are automatically revaluated as soon as a new instrument calibration is processed or when the station supervisors perform quality control. By analyzing data from 11 sites, we determined that the average calibration corrections are equal to 1.7 ± 0.3 µmol mol−1 for CO2 and 2.8 ± 3 nmol mol−1 for CH4. These biases are important to correct to avoid artificial gradients between stations that could lead to error in flux estimates when using atmospheric inversion techniques. We also calculated that the average drift between two successive calibrations separated by 15 days amounts to ±0.05 µmol mol−1 and ±0.7 nmol mol−1 for CO2 and CH4, respectively. Outliers are generally due to errors in the instrument configuration and can be readily detected thanks to the data products provided by the ATC. Several developments are still ongoing to improve the processing, including automated spike detection and calculation of time-varying uncertainties. |
| Databáze: | OpenAIRE |
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