Analysis of the Diurnal, Weekly, and Seasonal Cycles and Annual Trends in Atmospheric CO2 and CH4 at Tower Network in Siberia from 2005 to 2016
| Autor: | Aleksandr Fofonov, Denis Davydov, Toshinobu Machida, Mikhail Arshinov, Motoki Sasakawa, Boris D. Belan, Dmitry Belikov |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences greenhouse gas emissions methane carbon dioxide lcsh:QC851-999 Environmental Science (miscellaneous) Wind direction Seasonality 010502 geochemistry & geophysics Missing data Atmospheric sciences medicine.disease 01 natural sciences Wind speed TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES TRACER Greenhouse gas Temporal resolution medicine Environmental science lcsh:Meteorology. Climatology Tower 0105 earth and related environmental sciences |
| Zdroj: | Atmosphere Volume 10 Issue 11 Atmosphere, Vol 10, Iss 11, p 689 (2019) |
| ISSN: | 2073-4433 |
| DOI: | 10.3390/atmos10110689 |
| Popis: | We analyzed 12 years (2005–2016) of continuous measurements of atmospheric CO 2 and CH 4 concentrations made at nine tower observation sites in the Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION), located in Siberia. Since the data are very noisy and have a low temporal resolution due to gaps in instrument operation, we used the recently developed Prophet model, which was designed to handle the common features of time series (multiple strong seasonalities, trend changes, outliers) and has a robust performance in the presence of missing data and trend shifts. By decomposing each sampled time-series into its major components (i.e., annual trend and seasonal, weekly, and hourly variation), we observed periodically changing patterns of tracer concentrations. Specifically, we detected multi-year variability of tracers and identified high-concentration events. The frequency of such events was found to vary throughout the year, reaching up to 20% of days for some months, while the number of such events was found to be different for CO 2 and CH 4 . An analysis of weather conditions showed that, in most cases, high-concentration events were caused by a temperature inversion and low wind speed. Additionally, wind directions were found to be different for high- and low-concentration events. For some sites, the wind direction indicated the location of strong local sources of CO 2 and CH 4 . As well as elucidating the seasonality of greenhouse gas concentrations, this study confirmed the potential of the Prophet model for detecting periodicity in environmental phenomena. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|