In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of obervatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. We will provide a comprehensive description of the state of the regional Arctic system with respect to these variables, its overall regulation and controlling features and its interation with the global system.
In support of these objectives, a 3m eddy covariance station was established on Imnaviat Creek, Alaska. This station has been continuoulsy monitoring carbon dioxide, water vapor, energy fluxes and various micrometeorological variables.
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There are two types of data that are collected from each flux station involved in the AON project: high frequency eddy covariance (EC) data and low frequency means of meteorological and subsurface data. On a daily basis, approximately 75Mb of high frequency binary data and 16Kb of low frequency ASCII data is collected.
This station uses a CR3000 datalogger and a laptop to collect and store data. The CR3000 is used to measure the open-path EC equipment which is sampled at 10Hz. Mircrometeorlogical data is scanned at 0.33Hz and all datapoints are averaged every half hour. The CRBASIC program that controls the datalogger has been written in such a way that only the most basic corrections and filtering are applied to the raw data. These would include shifting the CSAT3 and LI7500 data arrays by 2 and 3 scans respectively to account for the inherent processing delays of these sensors.
About Data Processing
Time is expessed as local time, AST (UTC-9hrs) for Imnavait and MAGST (UTC+12hrs) for Pleistocene Park
Gas and energy fluxes are calculated from the high frequency time series using EdiRe or EddyPro software with these basic corrections: despiking, coordinate rotation, spectral correction, the 'WPL' correction, and the 'Burba' correction (where appropriate, to account for instrument heating effects).
Some data have been filtered (_f) and gap-filled (_gf).
The generation of mass and energy fluxes from the high frequency data is performed with the following basic corrections:
The 'WPL' correction
A coordinate rotation
A spectral correction
The 'Burba' correction (where appropriate to account for instrument heating effect)
*Correct instrument lag adjustment occurs during datalogging
The following QA/QC variables are applied to the flux data:
Gas analyzer diagnostics are used as a QA/QC variable for both flux and radiation data
Rejection angles of 10° at Imnavait and 45° at Pleistocene Park are used when EC instruments were downwind of tower to remove flow distortions
The flux and meteorological data is further post-processed to accomplish the following:
Data are within engineering specifications of each instrument.
Removal of impossible measurements (e.g. negative precipitation)
Removal of outliers via a three-standard deviation filter
Removal of unrealistic changes in a time series with a step change filter
A similarity filter to remove errors from instruments that generate a string of identical values when not working
Flux variables are calculated using Licor's EddyPro flux processing software. The quality control flags for flux variables (either raw or filtered) are calculated using the Mauder and Foken (2004) method within the EddyPro. Flag values and meanings are available on the Licor web site at https://www.licor.com/env/help/eddypro/topics_eddypro/Flux_Quality_Flags...
Gaps in the data are filled using the BGC_Jena gapfilling tool ReddyProc. Information on the gap-filling protocol is available here, https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWebGapFilling. The meaning of the quality control flags for all gap-filled (_gf) variables is listed here (https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWebOutput) under the _fqc entry.
See the file 2017_IC_1523_metadata_20171231.csv for data collection statistics.
Mar 2019-Version 1: Dataset first available
June 2019-Version 2: Updated metadata, removing abbreviations. Added detail to site descriptions. BK