Variables and formats available

Continuous Level2 data

Level2 data are original data submitted by the PI and checked/filtered only for out-of-range values or clearly wrong data. The variables available are listed in the table here below and are provided as ASCII file with missing values reported as -9999 and timestamp indicating the end of the averaging period. The file produced has in the first line the variables codes.

Level3 and Level4 data

The Level3 data are standard files with a selected number of variables with NEE calculated (Fc+Sc) and quality flags related to spikes and ustar filtering. Only flags are added and the data are not changed. The instead Level4 data are filtered, gapfilled and partitioned and aggregated at different time resolutions, from halfhourly to yearly.

The data are provided as ASCII files and as Matlab files. It is possible to download an example of Level3 and Level4 data, including the data description, here below:

Download a Level3 data file

Download a Level4 data file

Ancillary data

The ancillary data available are listed in the table below. These variables have a number of qualifiers that provide additional information (e.g. SOIL_C has as qualifier the uncertainty, the measurement depth, the reference date, possible comments…) and that are automatically added to the output file; a list of the existing qualifiers for each variable is available here. Ancillary data are provided in ASCII files with six columns:

• idVar: it is an integer number that identifies variables and qualifiers that are linked (see below the example)

• Variable: it is the variable code as in the table below

• Qualifier: a parameter related to the variable (e.g. the error or the method). It is "VALUE" when the variable value is reported.

• Value: the value of the variable or variable+qualifier; can be numeric or text depending of the nature of the qualifier

• Date: measurement or reference date in the format YYYYMMDD can be also only YYYYMM or YYYY when needed

• Time: time of the measurement, when relevant, in the format HHMM

In the example below it is explained how to use and interpret the idVar; supposing to have two measurements of LAI, the same day, but with different methodologies. The Qualifiers are the Value, Sigma, Technique and Comment and are present in both the measurements. The idVar helps to identify which Value, Sigma and Comment are related to the two methodologies used. In the example, the records with idVar = 16 are related to the LI-2000 technique while the LAI measured using hemispherical photos are identified by the idVar = 17. An example of Ancillary data file is available here.