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ECO2S

An overview of the Graphical User Interface

15 October 2010

Compiled by

Gerardo Fratini

Antonio Forgione

Department of Forest Sciences and Resources, University of Tuscia, Viterbo, Italy

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Contents

Abstract ................................................................................................................................................ 6

1. ECO2S Start Menu ....................................................................................................................... 7

::Data Logging ............................................................................................................................. 7

::Data Processing.......................................................................................................................... 7

2. ECO2S Menu bar (1) .................................................................................................................... 8

File Menu ......................................................................................................................................... 8

View Menu ....................................................................................................................................... 8

Start Menu .................................................................................................................................... 8

Project Page.................................................................................................................................. 8

Managed/Unmanaged mode ........................................................................................................ 9

Full screen .................................................................................................................................... 9

Status bar ...................................................................................................................................... 9

3. Project Page................................................................................................................................ 10

Raw File Type ............................................................................................................................ 10

Number of ASCII header lines................................................................................................... 11

End of line .................................................................................................................................. 11

Number of bytes per variable ..................................................................................................... 11

Endianess ................................................................................................................................... 11

Custom configuration file .......................................................................................................... 11

Raw file name format ................................................................................................................. 12

Use dynamic parameter file ....................................................................................................... 12

Use ECO2S::Datalogging project file ........................................................................................ 12

Next ............................................................................................................................................ 13

4. Processing Suite Page ................................................................................................................ 14

5. ECO2S Menu bar (2) .................................................................................................................. 15

Tools........................................................................................................................................... 15

Window ...................................................................................................................................... 15

6. ECO2S::RawProcess .................................................................................................................. 16

General Options Tab ...................................................................................................................... 16

Raw data directory ..................................................................................................................... 16

Output directory ......................................................................................................................... 16

Flux averaging interval .............................................................................................................. 17

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Number of files to merge ........................................................................................................... 17

Create continuous dataset........................................................................................................... 17

Missing lines allowance ............................................................................................................. 17

Settings Tab.................................................................................................................................... 19

Wind speed measurement off-set ............................................................................................... 19

Cross-wind correction for sonic temperature ............................................................................. 19

Angle-of-attack correction for wind components (Gill’s only) ................................................. 19

Axis rotation for tilt correction .................................................................................................. 20

Detrending .................................................................................................................................. 21

Time-lag compensation .............................................................................................................. 21

Output all binned (co)spectra ..................................................................................................... 23

Output full cospectra of sonic sensible heat ............................................................................... 23

Window for data tapering before fft-ing .................................................................................... 23

Number of frequency bins for spectra reduction ....................................................................... 23

Statistical Tests Tab ....................................................................................................................... 24

7. ECO2S::Meteo ............................................................................................................................ 28

General Options Tab ...................................................................................................................... 28

Meteo file(s) type ....................................................................................................................... 29

Data directory ............................................................................................................................. 30

File extension ............................................................................................................................. 30

Output directory ......................................................................................................................... 31

Timestamp refers to ................................................................................................................... 31

Date format ................................................................................................................................ 31

Time format................................................................................................................................ 31

Field separator ............................................................................................................................ 31

Separator policy ......................................................................................................................... 31

Variable Options Tab ..................................................................................................................... 32

8. ECO2S::Tilting ........................................................................................................................... 34

General Options Tab ...................................................................................................................... 34

Level 4 statistics file .................................................................................................................. 34

Output directory ......................................................................................................................... 34

Starting and ending date/time of dataset .................................................................................... 35

Missing lines allowance ............................................................................................................. 35

Number of wind sectors ............................................................................................................. 35

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Minimum number of elements per wind sectors ........................................................................ 35

Maximum average w (per input file) .......................................................................................... 35

Minimum average u (per input file) ........................................................................................... 35

Time-varying info file ................................................................................................................ 36

9. ECO2S::Spectra .......................................................................................................................... 37

General Options Tab ...................................................................................................................... 37

Binned (co)spectra directory ...................................................................................................... 38

Raw fluxes file ........................................................................................................................... 38

Output directory ......................................................................................................................... 38

Use external meteo data file ....................................................................................................... 38

Use external virtual meteo data file ........................................................................................... 39

Number of bins of reduced spectra ............................................................................................ 39

Minimum number of spectra samples in each frequency bin .................................................... 39

Minimum sensible heat flux ....................................................................................................... 39

Groups Tab ..................................................................................................................................... 41

10. ECO2S::Fluxes........................................................................................................................ 43

General Info Tab ............................................................................................................................ 43

Level 7 statistics file .................................................................................................................. 43

Output directory ......................................................................................................................... 44

Create continuous dataset........................................................................................................... 44

Time-varying info file ................................................................................................................ 44

Use external meteo data file ....................................................................................................... 44

Processing Options Tab ................................................................................................................. 45

Axis rotation for tilt correction .................................................................................................. 45

Compensation of density fluctuations ........................................................................................ 46

Add Li7500-related sensible heat components .......................................................................... 46

Correction of sonic temperature for humidity ............................................................................ 47

Spectral Corrections Tab ................................................................................................................ 48

High-pass filtering correction .................................................................................................... 50

Post-processing Options Tab ......................................................................................................... 51

Quality check ............................................................................................................................. 51

Footprint estimation ................................................................................................................... 52

References .......................................................................................................................................... 53

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blank page

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Abstract

In this document we provide a quick-look guide describing ECO2S Graphical User Interface (GUI).

The document is intended to help the user to understand the meaning of each entry, in order to

perform a proper Eddy Covariance (EC) processing, according to the data type and to the EC

site/set-up under consideration. The structure of ECO2S and its flow of data processing are

described in a separate document: “ECO2S – A quick introduction and user reference”, to which the

present guide refers often.

Note: In the present version of this document, the tool ECO2S::Timelag is not described, due to

time limitations. However, a quick look to ECO2S::Timelag and ECO2S::RawProcess will show

that there are minor differences between the two. ECO2S::Timelag requires a subset of the settings

of ECO2S::RawProcess. The only new entry here is Use external meteo data file, also described at

p. 38 in the context of ECO2S::Spectra.

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1. ECO2S Start Menu

::Data Logging

This is the main entrance to the ECO2S::Datalogging program. This is a fully-featured program to

acquire Eddy Covariance data. However, currently this software is not embedded into ECO2S

Graphical Interface, thus the button is ineffective. ECO2S::Datalogging is available as a separate

program, distributed on demand with the old name of ECO2Catch.

::Data Processing

This is the main entrance to ECO2S::Dataprocessing. This program allows you to process raw Eddy

Covariance data, to get corrected fluxes and a number of optional outputs, useful for further micro-

meteorological analysis.

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2. ECO2S Menu bar (1)

ECO2S features a rather limited Menu, with standard options that allow you to work with “project

files”, change a few settings and preferences, arrange project windows.

File Menu

As described more in depth in “ECO2S – A quick introduction and user reference”,

ECO2S::Dataprocessing is organized in “processing projects”. Each processing project files retains

all choices made by the user on which data to process and how to process them. You can handle

project as usual: New Project, Open, Open Recent, Save, Save as, Close act on the project file in the

common way. ECO2S project files are plain text files organized in INI format. Refer to the quick

introduction document for more details. The “Quit” button closes ECO2S.

View Menu

Start Menu

Click here to return to ECO2S Start Menu.

Project Page

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Takes you to the Project Page, where you enter general information, common to all following

processing steps.

Managed/Unmanaged mode

Not yet active, this option will allow to work in “supervised mode” (managed) or “expert mode”

(unmanaged). In “supervised mode” several options will be disabled and ECO2S will make some

choices for you, depending on your Eddy Covariance set-up and on the raw files. This is intended to

guide inexpert (or undecided) users to process data in a relatively safe way. The “expert mode” will

turn on all options and all their combinations, thereby also allowing more flexible usage, but also

exposing to unsuitable or even incorrect procedures.

Full screen

Shows ECO2S window on full screen.

Status bar

Shows/hide the status bar, where some activity logging is shown, along with the current date and

time and with the software version.

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3. Project Page

When you enter ECO2S::Dataprocessing, you are first introduced to the “Project Page”, where you

are asked to enter some general information, common to any following data processing. Here you

enter a Title and an ID for the current processing project. Note that the ID will be attached to all

output file names, thus you’d better choose a short one.

Raw File Type

Select here the type of raw files you are going to process. Several options are available:

Standard Ene: raw files created by ECO2Catch, refer to “ECO2S – A quick introduction

and user reference” for an introduction to this raw file type.

Native Streams: unmodified anemometric data streams. Native Streams can be collected

using ECO2Catch, but also with any simple serial monitor. In this release, supported Native

Streams are those from R3, HS, WindMaster sonics by Gill Instruments ltd. (Lymington,

Hampshire, England) and USA-1 by Metek GmbH (Elmshorn, Germany). Native serial

binary streams from the CSAT-3 by Campbell Scientific Inc. (North Logan, UT, USA) will

be supported starting from the next release.

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Generic ASCII: select this option to process raw files available as (not too complicated)

ASCII tables. Comma-, semi-column-, space- and tab- separated data columns are

supported.

Binary Alteddy: binary files generated by Alteddy.

Binary EddySoft: SLT files generated by EddyMeas, the data acquisition tool of the

EddySoft package by the Max Planck Institute for Biogeochemistry, Jena, Germany.

Binary EdiRe: SLT files generated by EdiRe data software by the University of Edinburg,

Edinburg, UK. Note that EdiRe and EddySoft SLT files differ mainly for the format of the

binary header.

Generic binary: generic binary format, for which details must be specified in the right

column (see below). This feature is still an “alpha version”, please report any bug or

difficulty you may encounter while using it.

Number of ASCII header lines

Applicable to all binary formats, allows to specify an eventual number of ASCII header lines in the

raw files.

End of line

Line terminator for the ASCII header lines (for binary files).

Number of bytes per variable

Here you specify the number of bytes used for each data value (for binary files).

Endianess

Specify here the order of meaningfulness of the bytes in each binary word. If in doubt, refer to the

developer of your data acquisition software. Most of the times “Little endian” applies.

Custom configuration file

Applicable when either EddySoft or EdiRe SLT binary data files are selected, it prompts you to

select a configuration file that is needed to interpret and convert the raw files. For EddySoft files the

relevant CFG file (produced by EddyMeas at acquisition time) must be selected. For EdiRe files,

the configuration file is a “processing list” containing, at least, the “Extract” and “Linear”

commands for all variables contained in the raw files. Refer to the documentation of the two

software if in doubt.

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Raw file name format

Here you must provide a prototype for the raw file names that ECO2S will use to extract timestamp

information. Refer to “ECO2S – A quick introduction and user reference” for details on how to

provide such prototype.

Use dynamic parameter file

Use this checkbox, and the related “Load…” button, to select a file with time-varying site/station

parameters. This requires some more explanations. As already mentioned, ECO2S::Dataprocessing

is particularly suited to process ENE files. Each ENE file contains acquisition-time information

about the site (e.g. the height of the canopy) and the set-up of the Eddy Covariance station (e.g. the

measurement height). Such parameters can change along the dataset, e.g. think about the canopy

height of a crop field: if the user updated ECO2S::Datalogging settings with current values, any

change in the acquisition-time parameters is automatically accounted for, because each ENE file is

processed with its corresponding parameters. However, if you are processing raw files of any other

type, you cannot automatically associate different values of acquisition-time parameters to different

raw files. A way around, is to provide a file that contains the time series of acquisition-time

parameters, if those are known to change along the dataset under consideration. Such file must be

created (currently outside ECO2S, e.g. with a spreadsheet) in a predefined format, described in

“ECO2S – A quick introduction and user reference”.

Use ECO2S::Datalogging project file

Use this checkbox, and the related “Load…” button to provide ECO2S with the proper “acquisition

project file”. Several cases can be envisaged here (refer to “ECO2S – A quick introduction and user

reference” for a more comprehensive description):

You are processing ENE files and there are acquisition-time parameters changing along the

dataset: in this case, uncheck this option. Files will be processed using file-specific

acquisition-time parameters. It is the best way to process your data.

You are processing ENE files but acquisition-time parameters did not change during

acquisition of your dataset: in this case, you can speed up the processing procedure, by

doing this: 1) unzip any ENE file; 2) locate the INI file extracted for the ENE archive; 3)

Use the “Load…” button to select this file; 4) check in the right (multi-)panel that all

information have been retrieved correctly; 5) in case any information was not retrieved

correctly, change it as needed and save the “ECO2S::datalogging project file” using the

buttons on the bottom-right corner of the right panel. By doing so, ECO2S will not read

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acquisition-time parameters from each ENE file, rather will use those provided in the file

you just loaded. This will speed up the processing a little.

You are not processing ENE files: in this case you must use a (virtual) “ECO2S::datalogging

project file”; most likely you don’t have one, so you must fill completely the multi-panel on

the right side (if you were acquiring raw data with ECO2Catch, you would have entered the

same information at acquisition-time). For an overview of content of the right-side multi-

panel, refer to the “ECO2S – A quick introduction and user reference”. Once you have filled

at least all green (=mandatory) fields, save the file with the buttons on the bottom-right

corner. The saved file will appear on the “Load…” entry; such acquisition-time information

will be used for the processing, unless they are bypassed by the time-varying parameters file

(see Use dynamic parameter file).

Next

This button activates if all mandatory fields have been entered. It takes you to the suite of

processing software. The information you entered so far will be used by most of the following

software, so make sure everything is set correctly.

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4. Processing Suite Page

By clicking “Next” in the Project Page, you have been taken to the Processing Suite Page, the place

where you will actually process your data. Remember that you can go back to the Start Menu or to

the Project Page from the View Menu, as well as from the corresponding icons in the tool bar.

The Processing Suite Page is characterised by the Software Menu on the left side, where you can

select the software you want to use. As you can read in more details in the “ECO2S – A quick

introduction and user reference”, in ECO2S corrected fluxes are obtained from raw data through a

series of – at least – two steps: the raw data processing (performed by ECO2S::RawProcess) and the

flux calculation (performed by ECO2S::Fluxes). A number of other tools are available for: 1)

optimizing time-lag estimations (ECO2S::Timelag); 2) formatting high-quality meteorological data

(ECO2S::Meteo); 3) calculating planar-fit rotation matrices (ECO2S::Tilting) and 4) analysing

turbulence co-spectra (ECO2S::Spectra). When you enter the Processing Suite, you are prompted to

ECO2S::RawProcess that is normally the starting point of the data processing. You can pass to

another tool by clicking on the related icon. Note that the “Run” button under the menu is

contextual, thus it will attempt to run the software that is currently active.

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5. ECO2S Menu bar (2)

Tools

The screenshot in the previous page shows ECO2S Output Console (the black window on the right),

that you can show/hide by checking/un-checking it from the Tools Menu in the Menu bar.

Window

Use options in this menu to arrange, visualize or close open windows. ECO2S is intended to be

multi-project, meaning that it will allow you to work on more than one processing project at a time.

Presently, however, known bugs related to this capability prevent a safe use, thus in this preliminary

release this option is switched off. The Window menu options are anyway fully operative.

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6. ECO2S::RawProcess

General Options Tab

As already mentioned, and described in more details in the “ECO2S – A quick introduction and user

reference”, ECO2S::RawProcess is the software that imports raw files and calculates main statistics

(such as mean values, standard deviations, covariances, skewness, kurtosis), that are used for the

calculation of corrected fluxes with ECO2S::Fluxes. It performs some standard Eddy Covariance

processing, such as de-spiking, cross-wind correction, angle-of-attack correction, 2D rotations for

tilt correction, time-lag compensation. In addition, it performs a thorough statistical screening of

raw time series reporting the corresponding flags, calculates tentative fluxes, derives values for

meteorological variables, calculates (on demand) spectra and co-spectra and performs the so-called

stationarity test.

In the General Option Tab, you provide some general information, listed hereafter. Remember that

green fields are mandatory.

Raw data directory

Use the “Browse…” button to locate the folder where your raw files are stored. If files are

organised in subfolders (e.g. monthly sub-folders), locate the parent folder and check the “Search in

subfolder” button. In this software version, depending on how raw files are named and organised in

folders, they might be processed in an order that is different than the chronological one. However,

an option is available for rearranging them in the proper chronological order (see “Create

continuous dataset” below). In the following release, files will be processed directly in

chronological order, regardless of their position or naming criteria.

Output directory

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Use the “Browse…” button to select the main output directory. Keep in mind that

ECO2S::RawProcess will create several subfolders in the selected parent folder and put output files

in there. Note also that this field, similar to output directories in other parts of the suite, is editable

directly from the GUI, without the need of using the “Browse…” button. When editing in such a

way, make sure that the path you type is compatible with your OS file system.

Flux averaging interval

Enter here the time period over which you want fluxes to be averaged, in minutes. Flux averaging

intervals can different from the duration of the raw files. Refer to “ECO2S – A quick introduction

and user reference” for details on how to better exploit your data files and get fluxes averaged over

any time period. Entering 0 (zero) minutes will cause ECO2S::RawProcess to process considering

the duration of each raw file as the flux averaging period.

Number of files to merge

Specify here how many files shall be merged and considered as one only file, for the purpose of

flux computation. This entry must be harmonized with the Flux averaging interval, as better

explained in the “ECO2S – A quick introduction and user reference”.

Create continuous dataset

If checked, ECO2S::RawProcess attempts to create a dataset going from the date/time of the first

raw file, to the date/time of the last one, using the “Flux averaging period” as a time step. Hence,

keep in mind that the very first (in a chronological sense) raw file should have a “correct”

timestamp, with respect to the time series you have in mind. If there are not enough data for

calculating fluxes for any time step, ECO2S::RawProcess will fill the corresponding output line

with an error code. Finally, checking this option forces the software to organize output data lines

chronologically. If the option is unchecked, instead, output files will contain only data lines

corresponding to time periods for which enough data are available for calculating corresponding

fluxes. However, in the current release we cannot assure that in all conditions the data lines will be

ordered chronologically. This will surely be the case when alphabetic and chronological orders

match, but in other cases – such as when files are organised in subfolders – the alphabetic order

may be prioritized. In both case (option checked or unchecked) ECO2S::RawProcess will

automatically adjust timestamps of files that are not coherent with the timeline defined by the flux

averaging period, so that the time structure of the output datasets is regular.

Missing lines allowance

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Each raw file will be tested for the number of data lines contained. Select here the maximum

amount of missing line (in percent) that is acceptable. Raw files with a larger amount of missing

lines will be ignored.

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Settings Tab

In this tab you make choices on how to process raw files.

Wind speed measurement off-set

If you know a systematic bias in the determination of any wind speed components, you can allow

ECO2S::RawProcess to account for it by specifying it here.

Cross-wind correction for sonic temperature

Check this option if you want ECO2S::RawProcess to apply the cross-wind correction to the

estimated sonic temperature. The correction is applied at the raw data level - that is, sample by

sample - after (Liu et al., 2001, Eqs. 3-9). However, the “humidity correction” term of their Eq. 3 is

not applied here, rather it is postponed and applied on the statistics that involve sonic temperature,

following a suggestion by (van Dijk et al., 2004, p. 36). Note that several anemometer models

include the correction in the firmware, so that the output temperature is already compensated for

cross-wind. In this release, it is left up to the user to avoid double accounting, by assuring coherence

between the anemometric measurement and the processing settings.

Angle-of-attack correction for wind components (Gill’s only)

The angle-of-attack correction refers a procedure that attempts to eliminate the error in the wind

speed measurements, due to an imperfect (co)sine response of the anemometer. This imperfection is

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due mostly to the self-sheltering of the transducers and to the flow distortion induced by the frame

of the anemometer. The correction, currently available only for Gill’s anemometers (WindMaster,

WindMaster Pro, R2, R3 and R3-50, R3-100), is implemented after (Nakai et al., 2006, Eqs. 3-6),

and the routine used is derived from the original routine available in Taro Nakai’s web page,

patched to be embedded in ECO2S. It is worth to underline that the application of this correction is

virtually independent (Taro Nakai, personal communication) from the internal correction “applied

to calibrate out the affects of the transducers and head framework” (cited from the R3/R3A User

Manual, Gill Instruments Ltd.). Thus, whether you acquired “CALIBRATED” or

“UNCALIBRATED” wind components, you may decide to apply the present correction as well.

Axis rotation for tilt correction

Tilt correction refers to the procedure that attempts to compensate for the misalignment of the sonic

anemometer with respect to the local streamlines coordinate system. Four options are available in

ECO2S::RawProcess, all implemented after (Wilczak et al., 2001):

DR on raw data (before detrending): double-rotation about the z and y axis, to nullify the

vertical and lateral wind components and align the x-axes with the (run-specific) mean wind

vector. The procedure is applied following (Wilczak et al., 2001, Eqs. 22-29). If you choose

this option, rotations are applied at the raw data level, before the time series are detrended.

DR on statistics (after detrending): same rotation as above, but not applied to the raw data,

rather directly to the relevant statistics (mean values and covariances).

TR on statistics (after detrending): include the DR on statistics, plus a third rotation to

nullify the cross-stream Reynolds stress, following (Wilczak et al., 2001, Eqs. 30-33).

Planar fit (after detrending): this is an alternative way to align the coordinate system to

the (long-term) mean local streamlines. It is implemented here following (Wilczak et al.,

2001, Eqs. 35 and 42-47).

Note that selecting a method applied on statistics (all but the first one), causes ECO2S::RawProcess

not to perform any rotation. In fact, these rotations are applied later, by ECO2S::Fluxes. This is

because ECO2S::RawProcess is intended to act on the raw data in order to calculate well defined

statistics. Any further processing is done in subsequent steps. Thus, the main difference between the

first and the second method, is that the second is applied after time series have been detrended.

Rotation angles, however, are always calculated with un-detrended wind components.

If you do not want to correct for such possible problem, uncheck this entry.

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Detrending

Detrending, or high-pass filtering, can be performed in ECO2S::RawProcess, by any of the

following four options:

Block average: it is the simple act of subtracting mean values from the time series,

calculated on the whole averaging period.

Linear detrending: consists in calculating fluctuations of each variable about a linear trend,

calculated on the whole averaging period.

Running mean: a local mean is defined at each time step by:

)(1

1 niiii vvn

vv (1)

In Eq. (1) as each new number is added into the average, the one n before is dropped out of

it, so each new number is the average of the last n old numbers. n is defined by the filter

time constant , expressed in seconds: afn , with af being the acquisition frequency

(Hz). Fluctuations are then calculated around such local mean values.

Exponentially-weighted average: similar to the previous one, but here the local mean is

defined by the weighted average of the current data point and the previous average:

1)1( iii vavav (2)

with the weight a given by the exponential:

t

ea

(3)

where is again the filter time constant and aft /1 .

Note that the last two methods require you to enter a “filter time constant”, that gets a different

meaning in the two cases. In both cases, the higher the time constant, the smaller the frequency

range that the filter cuts off.

Time-lag compensation

This entry provides several methods to compensate the time-lag between anemometric and gas

concentration time series, that might be due to several reasons (transient time of gases into a

sampling line, sensors separation, electronics delays). Depending on the causes of the possible time-

lags, different options might be more suited:

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Do not compensate: if you uncheck this entry, no time-lag compensation will be performed.

This choice, that helps speeding up the data processing, might be suitable only in case of

wind/concentration sensors placed very closed to each other, with rather sustained winds

that minimize the transit time between the sensors and with gas analysers that do not need a

sampling line to take the air parcels to the measuring cell.

Constant: this is a preferred option over the previous one, in the same situations described

above. You have already set a tentative time-lag for each of the gases in Project Page (or at

acquisition time in case of ENE files). This values will be used to synchronise wind and gas

concentration time series. This option might be suitable also for a not-so-accurate flux

calculation (e.g. for checking the status of the acquisition), in case of larger time-lags

induced by the presence of a sampling line, typical of closed-path gas analysers.

Max covariance with default: this is the most common way to determine and compensate

the time-lags. With this procedure, also referred to as “circular covariance”, the best time-

lag estimation is determined by maximizing the covariance between the vertical wind speed

and the gas concentration time series, within a range of plausible time-lags, defined by the

minimum and maximum time-lags you have set in the Project Page (or at acquisition time in

case of ENE files). If a maximum is not attained for the covariance within the window of

plausible time-lags (that is, if the series of covariances is monotone), a default value is used,

that is the one you set as the nominal time-lag in the Project Page.

Max covariance without default: same as above, but here the time-lags corresponding to

the maximum covariance are used in any case, even if covariances are monotone functions

of the plausible time-lags. In such cases the maximum covariance is found at one extreme of

the time-lag window and corresponding time-lag is either the minimum or the maximum

that you have set in the Project Page. The difference between this method and the former

one is probably not critical for narrowed time-lag windows, but it becomes more and more

important (and correspondingly affects fluxes) as the range of plausible time-lags becomes

larger.

Time-lag optimiser: this option requires you to run, first, ECO2S::Timelag. This software,

specifically designed for determining water vapour time-lags in closed-path EC systems,

attempts to calculate a functional relation (an exponential one) between the best time-lag

estimation - and of the plausible time-lag window - and ambient relative humidity, that

largely affects the dynamic of water vapour inside the sampling line (Ibrom et al., 2007a;

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Ibrom et al., 2007b). In doing this, it also provides best estimates for CO2, as well as proper

plausible time-lag windows. If you choose this option, after running ECO2S::Timelag you

must provide here the “Time-lag optimizer file” (the main output of ECO2S::Timelag) as

well as the relevant meteo file, from which relative humidity values are retrieved.

Output all binned (co)spectra

Check this option if you want ECO2S to calculate spectra and cospectra for all relevant variables

and fluxes. This option, that considerably increases the processing time (about 70% longer), must

be selected if you want to apply certain spectral correction schemes for low-pass filtering

correction. This issue is particularly critical for closed-path systems, although open-path systems

are not unaffected by high-frequency losses.

Output full cospectra of sonic sensible heat

This option, also indispensable in case of certain spectral correction schemes available in

ECO2S::Fluxes, is meant to output the full (i.e., not binned) co-spectrum of vertical velocity with

sonic temperature, that – assuming spectral similarity – can be considered as a reference

atmospheric cospectrum for all passive scalars, with the property of being unaffected (or minimally

affected) by artificial high-frequency attenuation.

Window for data tapering before fft-ing

If you selected either spectral output, here you can select the shape of the filter applied to the time

series before calculating their Discrete Fourier Transforms. The time-domain data windowing, or

tapering, is meant to reduce the among-frequencies leakages while estimating discrete spectra.

Different window shapes trade off in different ways between the peakedness and the narrowness of

the leakage function, although the final effects are rather similar to the purposes of micro-

meteorological analyses. For a thorough discussion of the topic see, e.g., (Press et al., 1996 Ch. 13,

pp. 545 – 549).

Number of frequency bins for spectra reduction

Set here the number of (logarithmically equally spaced) frequency bins for reducing spectra and

cospectra. The binning procedure is primarily meant to eliminate much of the medium and high-

frequency noise to highlight main slopes of (co)spectra. It also has the important side effect of

dramatically reducing the amount of disk space required to store spectral data, while retaining most

the information contained in it.

24

Statistical Tests Tab

This part of the GUI is devoted to the statistical tests that can be performed on the raw time series.

All tests here are implemented after (Vickers and Mahrt, 1997 Par. 6). Tests are selectable on the

left side of the tab. Use the “Select/Deselect All” checkbox for a quick selection. Note that in this

release, tests are implemented only for anemometric variables and for CO2/H2O time series (i.e., not

for methane and nitrous oxide). Where applicable, each time series gets a separate flag from each

test. There are cases, however, when the test is applied only to certain variables, or variable

combinations. Test results are presented as “hard flags” and “soft flags”, defining severe and

moderate deviations from ideal, respectively. For their detailed definition for each test refer to

(Vickers and Mahrt, 1997).

Results of the tests shall be used to take decisions about retaining or discarding the results obtained

from each raw file. ECO2S::RawProcess will not discard time series according to the test results, it

is left up to the user to do so on the final outputs. This is because criteria of selection policy are

hardly defined and partly subjective. Furthermore, reasons for hard-flags should be evaluated in

details, because sometimes unusual but yet plausible conditions may lead to artificial hard-flags

(Vickers and Mahrt, 1997).

All tests have some parameters that can be changed by the user in the corresponding sub-tab, while

other parameters have been hard-set in the code, to trade-off flexibility and complexity of the

interface. However, we appreciate suggestions in this respect. ECO2S::RawProcess proposes default

25

values for all settable parameters, based on the reference paper. However, users should customize

those values according to their EC set-up and site characteristics. ECO2S::RawProcess defaults can

always be restored by clicking the “Set Defaults” button on the bottom right corner. Here it follows

a brief description of the tests:

Spike detection/removal: selecting this option, time series will be tested for the number of

spikes and flagged if this number is beyond a certain (user selectable) threshold. In doing so,

spikes are removed and replaced by linear interpolation of neighbouring data points. In the

GUI you must set:

o Max consecutive outliers: maximum number of consecutive outliers to

define a spike. If more than n consecutive data points are found outside the

plausibility range, they are not detected as a spike;

o Plausibility range: the amplitude of the range around the window mean,

expressed as multiples of the window standard deviation;

o Accepted amount of spikes: The percentage of spikes, respect to the total

number of data points, defining the threshold to flag the each variable.

Amplitude resolution: this test assesses whether the number of different values that each

variable takes throughout the time series covers homogeneously enough the range of its

variations. This range is defined by the minimum among: 1) the difference between the

maximum and the minimum value assumed by the variable and 2) n times the standard

deviation of the variable in the time series. Here you must set:

o Range of variation: The multiples of the window standard deviations (n)

defining the range of variations for each variable;

o Number of bins: The number of bins in which the range of variation must be

divided;

o Accepted amount of empty bins: The percentage of empty bins over

which each variable is flagged for a too low amplitude resolution.

Drop-outs: this test detects whether each variable temporarily sticks on some value

throughout the time series. It is assessed by considering if how many consecutive data points

stay in the same bin (as defined above). Extreme bins (as opposed to central bins) are

expected to have smaller numbers of consecutive data points, thus thresholds are defined

differently for extreme and central bins. You must set:

26

o Percentile defining extreme bins: The percentile that distinguishes

extreme vs. central bins. For example, choosing 10%, the central bins will be those

between the 10th

and the 90th

percentiles. The remaining bins are considered as

extreme bins.

o Accepted central drop-outs: The threshold percentage of central drop-

outs, beyond which the variable is flagged for too many drop-outs;

o Accepted extreme drop-outs: The threshold percentage of extreme drop-

outs, beyond which the variable is flagged for too many drop-outs.

Absolute limits: tests the time series for single values exceeding plausible physical ranges.

Here you must set:

o Max horizontal velocity: the maximum plausible horizontal velocity,

calculated from the combination of the two wind components in the anemometer’s

coordinate framework.

o Max vertical wind component: the maximum plausible vertical wind

component. Note that the very raw vertical wind component is used here, before any

compensation for tilt correction. This implies that if the anemometer is sensibly tilted

with respect to local streamlines, a part of the horizontal component may folds into

the vertical one, that would thus result seriously biased. This means that an important

sequence of raw files flagged for too high vertical wind, might be a sign of an

improper installation of the anemometer.

o Min/Max Ts: maximum and minimum values of sonic temperature, used as a

proxy for air temperature. Set these values large enough to include plausible extreme

values. Consider that the test is performed on the raw data, not on 30 min average

values.

o Min/Max CO2/H2O concentration: set here plausible ranges of gas

concentrations (expressed as mole fractions), considering the peculiarities of your

site.

Skewness and kurtosis: selecting this test, skewness and kurtosis for the whole time series

are evaluated against acceptance ranges that you must set in the GUI. In the GUI you set:

o Lower/Higher limits for hard/soft flagging for

skewness/kurtosis: maximum and minimum accepted values for the statistical

27

moments. Limits for hard-flags shall contain those for soft-flags. Default values are

those suggested by (Vickers and Mahrt, 1997).

Discontinuites: discontinuities in the time series are detected using the Haar transform that

calculates the difference in some quantity over two half-window means. Large values of the

transform identify changes that are coherent on the scale of the window and hence

potentially detect discontinuities that lead to semi-permanent changes as opposed to sharp

changes associated with smaller-scale fluctuations (Vickers and Mahrt, 1997). In the GUI

you must set the limits for hard- and soft-flagging individual variables for discontinuites.

Refer to the cited publication for more details.

Time-lags: this test flags CO2/H2O time series if the maximal w-covariances, determined

via the covariance maximization procedure described above (see the “Max covariance with

default” option for time-lag compensation) and evaluated over a predefined time-lag

window, are too different from those calculated for the suggested time-lags. That is, the

mismatch between fluxes calculated with the expected time lags and with the “actual” time

lags is too large. In the GUI, you set acceptable percentage of mismatch to hard- and soft-

flag the file.

Angle-of-attack: if selected, this test calculates sample-wise angle of attacks throughout the

file and flags it if the percentage of angles-of-attack exceeding a user-defined range is

beyond a (user-selected) threshold.

Steadiness of horizontal wind: this test assesses whether the along-wind and cross-wind

components of the wind vector undergo a systematic reduction (increase) throughout the

file. If the quadratic combination of such systematic variations is beyond the limit that you

set in the GUI, the file is hard-flagged for instationary horizontal wind (cf. Vickers and

Mahrt, 1997, Par. 6g).

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7. ECO2S::Meteo

General Options Tab

This tool of ECO2S allows you to reformat high-quality meteorological files into a suitable format

that is importable by all other software of the suite. High quality meteo data are expected to be

available as values averaged over a certain time interval, typically - but not necessarily - 30 minutes

and to be provided as data lines featuring a timestamp at the beginning. ECO2S::Meteo is able to

import an undefined number of meteo files and to merge them into a unique time series, basing on

the timestamps. Note that the association of meteo data with all results calculated from raw data, is

done basing on the time stamp. Thus, make sure that the time series you implicitly define with the

Flux averaging interval and the time stamp of the first raw file, matches with the time series of the

data file. A smarter association of meteo data lines with results obtained from raw data is planned

for a next release.

ECO2S meteo file format is characterised by the presence of an header (where variable labels and

units are specified) by a standard (ISO) timestamp format and by the fact that all meteo files have

the same number of fields and the same order for all supported (meteo and auxiliary) variables. This

choice in general implies an abundance of useless “error codes” for the variables that are not

available in the original data files. However, for yearly datasets, the amount of disk space required

is negligible with respect to current computer capabilities. On the other side, this format allows a

straightforward usage of meteo files collected from different stations (or from the same station in

different configurations), within and outside ECO2S.

ECO2S::Meteo allows to reformat three different types of meteo files: files collected with Campbell

Scientific dataloggers (such as CR10x, CR3000, CR5000) and meteo files formatted according to

the specifications of the FLUXNET database, either in TXT or CSV style, as specified below.

29

Meteo file(s) type

Here you specify the type of meteo files you want to reformat.

Campbell dataloggers: choose this options if your meteo files have been collected with a

Campbell datalogger, with a format similar to that showed in Figure 1. In this release, the

format allowed for the meteo data of this file type is rather strict. ECO2S team is currently

working to make it more flexible.

Figure 1. Sample meteo file as acquired with a Campbell datalogger CR10x.

In this file type, the first field in each data line must be an alphanumeric identifier of the

datalogger, then the date follows in the form of year (4 digits), DOY (3 digits), time

(HHMM, but accepted also HMM and MM) and then the data values. In the example shown

in Figure 1 fields are separated by commas, but this is user-selectable (see below).

FLUXNET TXT form: it is likely that you have already submitted meteo files to the

FLUXNET databases. If so, you should be familiar with the standardized meteo data format

of this database; perhaps your meteo files are already formatted in either the TXT or CSV

style. Figure 2 shows an example of a meteo file formatted according to the TXT format:

Figure 2. Sample meteo file as formatted in FLUXNET-TXT style.

Here we recognize several elements: a two-lines header, where variable labels and units are

reported. Note that variable labels must be specified, as standardized in the FLUXNET

database otherwise they are not recognized by the software. On the contrary, the units line is

not interpreted. Data are expected to be expressed in FLUXNET standard units.

30

Data lines are expected to start with a timestamp, whose format can be specified in the GUI

(see below), and then continue with data values in the order specified in the header. Black

spaces are allowed between the field separator and the actual values. The field separator can

also be specified (see later).

FLUXNET CSV form: The main difference between the present format and the previous

one is the shape of the header. See Figure 3:

Figure 3. Sample meteo file as formatted in FLUXNET-CSV style.

All that ECO2S::Meteo requires is that the list of the variables is in the 4th

line and the actual

data lines start from the 10th

. For the rest, the file is treated in exactly the same way as a

FLUXNET-TXT file. In the following release, the distinction between the two file types will

be eliminated and more file description capabilities will be provided to the users.

Note that FLUXNET-CSV files can be obtained from Microsoft Excel native format (“.xls”),

by saving the data file (using Excel) as “values delimited by the list separator”. The actual

list separator depends on the Excel settings in your computer and it is likely to be comma,

semi-column, tab or space. You will be able to specify it to ECO2S::Meteo later on.

For both FLUXNET types, note that pressure is expressed in kPa, while ECO2S uses hPa.

As a consequence, ECO2S automatically and silently performs the conversion, assuming that

the pressure values read from the file are in kPa.

Data directory

Specify here the directory where ECO2S::Meteo will look for valid meteo files. The software will

attempt to import all files with the extension specified later. In the case of Campbell datalogger

files, the presence of the logger identifier will assure that extraneous files are ignored, while there is

not (yet) such control on either FLUXNET file types, so it is strongly suggested to create a separate

folder where only the meteo files of interest are collected.

File extension

31

Specify here the extension (without the “dot”) of the meteo files. All files with the specified

extension will be considered as valid meteo files. Where applicable, ECO2S::Meteo will attempt to

understand whether the file is actually a meteo one. Note, however, that in this software version the

control over improper files is not fully implemented, so finding extraneous files with the selected

extension may result in a software crash.

Output directory

Set the directory where you want ECO2S::Meteo to place its output, constituted by the reformatted

meteo file and by a log file of performed operations.

Timestamp refers to

Indicate here whether the timestamp of the meteo data lines refers to the end or to the beginning of

the averaging period. Remember that, if the case, ECO2S will modify the timestamps so that they

always refer to the end of the averaging periods. This is the policy adopted throughout the software

suite.

Date format

Only applicable to FLUXNET data files. Here you must specify the date format of the data lines.

For details on how to correctly describe timestamps, refer to “ECO2S – A quick introduction and

user reference”, in the section describing the definition of raw file name prototype.

Time format

Same as above, but for the time.

Field separator

Here you must specify which character shall be considered as the field separator in the data files.

Separator policy

This option is not implemented yet. It is intended to specify to ECO2S::Meteo how to behave in

case two or more consecutive separators are found. Currently, two or more separators are

considered as being only one.

32

Variable Options Tab

If you selected the “Campbell datalogger” as the meteo file type, now you have to specify the nature

and order of the meteorological variables in your file(s). Note that units cannot be chosen freely,

rather must match those specified in the GUI for each variable. This is especially critical for a

subset of meteo variables that are actually used by ECO2S and expected to be expressed in

predefined units. These are: air temperature (in °C), air pressure (in hPa), relative humidity (in %),

global radiation (in W m-2

), net radiation (in W m-2

) and PPFD (in mol m-2

s-1

). All other

supported variables might be present in your file with different units. However, consider that the

units reported in the output file header are those expected by ECO2S, thus having different actual

units would turn out in an inconsistency between the header and the content of the file. A much

better way would be to first convert units into ECO2S units, and then use ECO2S::Meteo to perform

the file format conversion. It is planned for a later release that ECO2S will allow to change variable

units, too. Finally, note that a maximum of 19 “custom” variables is available, to handle variables

that are present in your meteo files but that are not foreseen in the ECO2S standard set. For each

variable not belonging to the ECO2S set, select an “Optional” one. You will then find those

variables ordered as optional ones in the last 19 columns of the output meteo file. Currently,

ECO2S::Meteo does not allow entering explicit name/units for those variables. Keep this in mind

when storing your files somewhere for a later use: a small table with the correspondence of ECO2S

“Optional” variables and their actual meaning might help in the future. It is planned for the next

release, to allow the user to explicitly enter a name and units for variables beyond the standard set.

In the “Variable order” table you can add or deleted rows (corresponding to data columns in the

meteo file), by using the “+ Add a variable” and “- Remove a variable” buttons. The aim is to

describe the order of the variables as they come in the meteo file, excluding the timestamp that is

33

always expected to initiate the data line. When you click on the “+ Add a variable” button, a new

row is added (under the currently focused row or as the first row if none is focused) with the

message “PLEASE SPECIFY VARIABLE”: click there and specify the new variable. Add and

remove rows as needed if you enter the wrong sequence. Note that the GUI does not allow you to

enter the same variable name more than once. If you do have replicates of the same variable, where

applicable use the repetitions foreseen in the standard set (such as PPFD, PPFD2, PPFD3), or use

“Opt ##” names (with ## going from 2 to 20).

34

8. ECO2S::Tilting

General Options Tab

ECO2S::Tilting is primarily intended for calculating sector-wise planar fit rotation matrices, in the

framework of coordinate rotations for correcting anemometer tilting with respect to local

streamlines. It also outputs the fitting plane(s) coefficients on a separate file. ECO2S::Tilting starts

from an intermediate statistics file produced by ECO2S::RawProcess (statistics at Level 4) and

performs the calculations for a user-defined number of equally (angularly) wide wind sectors.

Below you can read more details about the GUI fields that must be entered prior of running this

tool.

Level 4 statistics file

Here you must select the appropriate statistics file, produced by ECO2S::RawProcess, to be used for

planar fit rotation calculation. Statistics at Level 4 are calculated on raw time series, after the de-

spiking, cross-wind correction and angle of attack correction (if any of these are requested). Note

that the planar fit matrices calculation requires only the mean (un-rotated) wind components in the

anemometer’s Cartesian coordinate system. Note also that ECO2S will pre-compile this field for

you with the appropriate statistics file, at the end of the ECO2S::RawProcess run. However, you are

always free to change that pre-selection using the “Browse…” button to load another file.

Output directory

35

Here you select the directory where to save the output files. Also this field is pre-compiled by

ECO2S, so that all output files from the same processing project are properly organized in one main

folder. However, same as above, you are always free to select a different output folder.

Starting and ending date/time of dataset

Planar fit calculations must be performed using wind data relating to a time period when the

anemometer was not moved and did not undergo major dislocations. Normally, a time period of 3 to

6 weeks is enough for calculating planar fit coefficients, depending on the number of sectors.

ECO2S::Tilting allows you to select the starting/ending timestamps of the time period used for

calculating planar fit coefficients, that of course must fall (at least partially) within the period of the

available statistics (that is, within the period of the processed raw files).

Missing lines allowance

Similar to the same setting in ECO2S::RawProcess. Each raw file will be tested for the number of

data lines contained. Select here the maximum amount of missing line (in percent) that is

acceptable. Raw files with a larger amount of missing lines will be ignored.

Number of wind sectors

Enter here the number of wind sectors for which you want to calculate rotation matrices, up to a

maximum of 32 sectors. Each sector has an angular wideness given by 360° divided by the selected

number of sectors. Sectors are numbered in clockwise direction, the first one starting from North

(0°). In principle, a higher number of sectors allows a better representation in complex topographies

but requires a higher number of statistics available.

Minimum number of elements per wind sectors

Planar fit calculation is performed for each wind sector, for which a minimum number of statistics

is available. This threshold must be specified here. For sectors for which rotation matrices are not

calculated because there are not enough data, in the next processing step ECO2S::Flux will

automatically switch to DR (double rotation) applied on statistics.

Maximum average w (per input file)

Here and in the following entry, you specify boundaries to acceptable values of average wind

components. Specifically, here you can set a maximum average vertical wind component.

Minimum average u (per input file)

Similar to the previous one but to set a minimum value for the horizontal wind speed.

36

Time-varying info file

If in the Project Page you checked the option for using a “dynamic parameter file”, or if you are

processing ENE files without using a common ECO2S::Datalogging project file, you will find this

field mandatory. Here you must enter the path of the file containing the time series of acquisition-

time parameters. This file, generated by ECO2S::RawProcess, is named eco2s_ID_ini_info.csv

(where ID is the ID of the project, that you entered in the Project Page) and is stored in the sub-

folder ..\eco2s_aux, automatically created inside the chosen main output folder. The file is

generated in any case, but it is only needed when there could be acquisition-time parameters

changing along the dataset. Once more, at the end of the ECO2S::RawProcess you should find this

field pre-compiled with the path of the file produced in the same run. You can however modify it at

your convenience.

37

9. ECO2S::Spectra

General Options Tab

This tool of ECO2S is used to perform an analysis of spectra derived from raw data, in order to

determine the cut-off frequencies of the eddy covariance system under consideration, for the

purpose of in-situ or mixed analytic/in-situ spectral corrections. The rationale of the analysis and

the details of the implementations follow closely the methodology proposed by (Ibrom et al.,

2007a). The tool focuses on the assessment of the attenuation of gas concentration spectra at the

high-frequency range, considering sonic temperature spectra as a proxy to the real gas spectra

(assuming spectral similarity). High-frequency attenuation is due to the sum of several factors,

some of which are inherent to the eddy covariance set-up (e.g., the finite time/space resolution of

instruments, the transit of air parcels through a sampling line), while others are attributable to the

micrometeorological conditions (e.g. relative humidity) or to the management of the flux station

(e.g. aging of the sampling lines, see Mammarella et al., 2009). Because the environmental relative

humidity was shown to be a major driver of spectral attenuation of water vapour signals in closed-

path systems, while it is not the case for CO2, ECO2S performs the spectral analysis in different

ways for the two scalars. For water vapour, using all available spectra, an ensemble cut-off

frequency is determined for ten relative humidity classes. Of course there are cases, when relative

humidity is not a major driver of spectral attenuation, for example when open-path gas analysers are

38

used. In such cases, ECO2S still determines a set of RH-dependent cut-off frequencies. This is not

harmful: simply, cut-offs will not show a detectable dependency on RH. A drawback, however, is

that a considerable amount of spectra must be available, given that they will be sorted in ten RH-

classes and then averaged to derive ensemble cut-off frequencies.

For CO2, instead, ECO2S allows to determine different ensemble cut-off frequencies for different

time periods, as specified below.

Similar to ECO2S::tilting, also ECO2S::Spectra starts from partial results created by

ECO2S::RawProcess. Running ECO2S::Spectra requires that you selected the option Output all

binned (co)spectra in ECO2S::RawProcess, because the tool uses those spectra for the calculations.

The main output of ECO2S::Spectra is a text file reporting the transfer function (TF) parameters for

H2O and CO2, for two different kinds of assumed shaped of the TFs, namely the “Infinite Impulse

Response” (IIR) filter (Ibrom et al., 2007a, Eq. 3) and the one-parameter sigma function described

by (Aubinet et al., 2001, Eq. A.2). In case the non linear regressions implied in the implementation

do not converge, or if there is not a sufficient amount of well characterised spectra, an error code is

returned in the output file. Results of ECO2S::Spectra can be used later, for the calculation of

corrected fluxes with ECO2S::Fluxes.

Similar to the other software in the suite, once ECO2S::RawProcess has completed the run, the GUI

pre-compiles in/out directories and file paths to drive a correct use. You can however always

change these paths using the buttons “Load…” or “Browse…”.

Binned (co)spectra directory

Select here the directory where binned (co)spectra have been stored by ECO2S::RawProccess. In the

normal case, this is a sub-folder named \eco2s_bin_cospectra inside the main output folder

selected in ECO2S::RawProccess.

Raw fluxes file

This file is also generated by ECO2S::RawProccess. It is a tentative calculation of uncorrected

fluxes. Here tentative fluxes of latent heat, sensible heat and CO2 are used to select spectra for

calculating transfer functions (see below).

Output directory

This is the directory where ECO2S::Spectra will put its output files.

Use external meteo data file

39

Check this option (and load the related file) if you have a high-quality meteorological file from

which ambient relative humidity and air temperature will be retrieved. Remember that meteo files

must be formatted using ECO2S::Meteo, before they can be used in ECO2S.

Use external virtual meteo data file

Check this option (and load the related file) if you do not have a high-quality meteorological file,

and thus need to use the meteo values estimated by ECO2S::RawProcess starting from raw files.

From this file, ECO2S::Spectra will retrieve “virtual” ambient relative humidity and air temperature

for its internal need.

Number of bins of reduced spectra

This information must match that set in ECO2S::RawProcess (Number of frequency bins for spectra

reduction). In a following release, the need to re-enter settings already entered elsewhere, will be

eliminated. For the moment, the GUI will take care of pre-compiling this field with the value you

entered in ECO2S::RawProcess.

Minimum number of spectra samples in each frequency bin

Ensemble, binned spectra are evaluated by averaging all available (binned) spectra, sorting them

into time-classes or RH-classes where applicable. If any bins do not contain a sufficient amount of

spectra samples, such bin is not considered in the following processing. Specify here such minimum

value.

Minimum sensible heat flux

Set here a minimum value for the sensible heat flux. Spectra of sonic temperature corresponding to

sensible heat fluxes smaller than the one you set here, will not be considered in the analysis. We

recall that sonic temperature spectrum is considered here as a proxy for the unaffected spectrum of

all atmospheric passive scalars, including gas concentrations.

Minimum (absolute) CO2 flux

Set here a minimum value for the carbon dioxide flux. Spectra corresponding to CO2 fluxes smaller

than this, will not be considered in the CO2 spectral attenuation analysis.

Minimum latent heat flux

Set here a minimum value for the latent heat flux. Spectra of water vapour corresponding to latent

heat fluxes smaller than this, will not be considered in the water vapour spectral attenuation

analysis.

40

Minimum frequency for fitting low-pass transfer functions

Currently, ECO2S::Spectra only assess spectral attenuations at the high-frequency range. Often, the

behaviours of CO2, H2O and temperature spectra at the low-frequency end differ from each other,

due to different source/sinks behaviours. Thus, when calculating low-pass transfer functions, it is

advisable to eliminate from the regressions the low-frequency range, that anyway is virtually not

affected by the phenomena that cause high-frequency losses.

Maximum frequency for fitting low-pass transfer functions

Spectra of scalar concentrations as measured by IRGAs often show high-frequency noise. Although

ECO2S automatically performs a high-frequency noise elimination, by linearly interpolating and

subtracting the high-frequency (>2Hz) part of ensemble spectra (see Ibrom et al., 2007a), you may

want to limit the calculation of transfer functions to a certain band, that you may possibly determine

by visual inspection of binned spectra calculated by ECO2S::RawProcess. Set here such higher

limit: if you want to consider the full (high frequency) spectral range, insert a large value here (e.g.,

the acquisition frequency will be large enough).

41

Groups Tab

As mentioned above, CO2 transfer functions can be evaluated for different time periods. This option

can be useful to account for the possible effects of , for example, sampling line aging and anyway to

analyse whether there is any systematic change in the spectral attenuation of CO2 signals. To do

this, ECO2S::Spectra allows you to create different “time groups” within a period of one year, with

a monthly base. You can create up to 12 groups, and each group can contain one to twelve months,

with the constrains that: 1) the same month cannot belong to more than one group and 2) groups

must be chronologically ordered. Some examples:

To create only one group including the whole year, select January/December as the

Start/Stop months of the first group. This is the default settings. In the output files, you will

then find the same transfer function parameters for all months.

To create four contiguous and equally long groups: Select January/March for the first group,

then Click on “Add a group” and select April/June, and so on. You will then find the same

transfer function parameters for the months belonging to the same group.

Also consider that:

1) groups do not have to be contiguous (if a month is not included in the groups, an error code

for that month will be reported as output).

42

2) groups can include months, for which you do not have data (spectra). Only groups for which

a sufficient amount of spectra is available will be considered in the calculations. For the

others, error codes will show on output.

43

10. ECO2S::Fluxes

General Info Tab

ECO2S::Fluxes is the last step of data processing, designed to calculate corrected fluxes, starting

from the results obtained in the previous steps. In the easiest case, the whole processing is done

using ECO2S::RawProcess and ECO2S::Fluxes. This is the case when: 1) you do not need to use the

planar fit method to correct for anemometer’s tilting; 2) you do not intend to use an in-situ

correction method for compensating high-frequency losses; 3) you do not have high-quality meteo

files and 4) time-lag estimation is not critical. In any other case, the processing will need to pass

also through one of the tools intended to: 1) calculate planar fit rotation matrices (ECO2S::Tilting);

2) perform a spectral analysis based measured spectra (ECO2S::Spectra); 3) format meteo files

(ECO2S::Meteo) and 4) assess relative-humidity dependency of water vapour time-lags as well as

calculate a plausibility range of time-lags for CO2 time series (ECO2S::Timelag).

We will see in the following how the results of the other software enter into ECO2S::Fluxes.

Level 7 statistics file

ECO2S::Fluxes starts its calculations from the last intermediate statistics file produced by

ECO2S::RawProcess. At this level, statistics are calculated on raw time series after: de-spiking (if

requested), cross-wind correction (if requested), angle of attack correction (if requested), double-

rotation for tilt correction (if requested); high-pass filtering; time-lag compensation (if requested).

44

The GUI pre-compiles this field (as well as all other file paths and directories, where applicable) at

the successful end of ECO2S::RawProcess run. You can always change the default path by using the

buttons “Load…” or “Browse…”.

Output directory

As usual, this is the directory where ECO2S::Fluxes will store its output files.

Create continuous dataset

Refer to the same option, described at p.17. If you have chosen this option when running

ECO2S::RawProcess, then doing it here is redundant (although not harmful).

Time-varying info file

Refer to the same entry described at p. 36.

Use external meteo data file

Refer to the same entry described at p. 38.

45

Processing Options Tab

Here you will select some processing choices. Some of them shall fit with previous choices, and the

GUI helps you to do so.

Axis rotation for tilt correction

Refer to the description at p. 20 for the available options and a brief explanation. Note that the GUI

here forces you to be consistent with the choices made in ECO2S::RawProcess, in the framework of

the same processing project:

If you selected the option DR on raw data (before detrending), the double rotation was

applied in ECO2S::RawProcess and no further rotation is allowed. Consistently, the GUI

shows you this as the only option available.

If you selected either DR on statistics (after detrending), TR on statistics (after detrending)

or Planar Fit, then ECO2S::RawProcess did not perform any rotation yet, so in principle here

you are able to choose any of the three, but of course not the DR on raw data (before

detrending), that is consistently dimmed and not selectable.

If you choose Planar Fit, the GUI turns on the mandatory entry Planar fit auxiliary file, that

asks you to enter the rotation matrix file produced by ECO2S::Tilting, recognized by the

name patterns: eco2s_ID_rotmat.txt, with the ID being the ID of the processing project you

entered in the Project Page (see p. 10).

46

Compensation of density fluctuations

This processing option refers to the compensation of air density fluctuations, induced by

temperature, water vapour and pressure fluctuations, that impacts largely carbon dioxide fluxes and,

secondarily, water vapour (hence latent heat) fluxes. The issue is treated in different ways,

depending on the nature of the gas concentration measurement:

If gas measurements are available as mixing ratios (mole gas per mole of dry air) from a

closed-path system, assuming effective dumping of temperature fluctuations in the sampling

line, there is no need for a density correction, as this measure of concentration is not affected

by dilution/concentration due to water vapour fluctuations (Ibrom et al., 2007b). Thus, in

this release of the software, fluxes are calculated from mixing ratios without any

consideration of air density fluctuations. In the following release, however, ECO2S will be

able to account for any expansion/contraction effects induced by residual temperature

fluctuations in the measuring cell of a closed-path system, provided that fast cell

temperature readings are available.

If gas measurements are available as mole fractions (mole of gas per more of humid air),

they are tacitly converted to mixing ratios, point-by-point, at the raw data level, by

ECO2S::RawProcess. Thus, in ECO2S::Fluxes they are treated exactly like the case above.

That is, air density fluctuations are neglected.

If gas measurements are available as mole density, typically the case with open-path gas

analysers, the so-called WPL formulation (Webb et al., 1980) is implemented to include air

density fluctuation effects.

Add Li7500-related sensible heat components

This option, available only for gas measurements taken with the Li-75001 by LI-COR Inc. (Lincoln,

Nebraska, USA), and if the WPL correction was selected, adds a contribution to such correction,

that accounts for extra air density fluctuations, induced by instrument surface heat exchange (Burba

et al., 2008). When only standard measurements are available from the li-7500 (i.e., no fast internal

temperature readings), the correction can be calculated starting from instrument surface temperature

estimations calculated either with a simple or a multiple linear regression(s) (see the cited

reference). Parameters of linear regressions should be assessed for each sensor unit and in each

1 Note that the correction shall not be applied to measurements collected with the Li-7500A.

47

configuration. However, values are available from ad ad-hoc campaign, which are valid within the

limits defined in (Burba et al., 2008). Those values are set by default in ECO2S::Fluxes. If you do

not have better (i.e., unit specific) estimations, such values – that you can retrieve any moment by

using the button “Set defaults” – are to be considered as the best option.

Correction of sonic temperature for humidity

This correction, often referred to as “Schotanus correction”, attempts to correct air temperature

estimations (and all related statistics) that are based on sonic temperature, for the effect of air

humidity on the latter (Schotanus et al., 1983). The humidity correction is applied in ECO2S

following the approach proposed in (van Dijk et al., 2004, p. 31, bullet 10.), that suggest to not

apply it at the raw data level, where individual inaccurate values of the humidity retrieved from fast

hygrometer readings might bias the overall correction. Rather, the correction is applied a posteriori

on averages and covariances. Two slightly different options are available:

Van Dijk et al. (2004): follows Eqs. 3.49 – 3.53 of the cited article.

Kaymal and Gaynor (1991): similar to the previous one, calculates the coefficient 0.51 in

Eq. 3.49 of (van Dijk et al., 2004) using a slightly different formulation (Kaimal and

Gaynor, 1991).

48

Spectral Corrections Tab

A separate tab is dedicated to the selection of the spectral correction procedure. Several options are

available, that might be suitable in different situations, depending mainly on the EC setup (analyser,

sampling line, sensors separation, height above the canopy), the ecosystem considered (crop, forest,

wetland) and its climatic conditions (wind regimes, frequency of occurrence of high relative

humidity).

Three methods are implemented following strictly three bibliographic references: a fully analytical

method (Moncrieff et al., 1997), an hybrid analytical/in-situ method (Horst, 1997) and a fully in-situ

method (Ibrom et al., 2007a). Moreover, ECO2S features an original method, that attempts at

refining the one by Ibrom and co-authors. A second original method is under development, visible

in the GUI (labelled as ECO2S II), but not selectable. A brief overview of the options available is

presented hereafter:

Moncrieff et al. (1997): Following the approach presented in (Moore, 1986), this method

attempts to describe the EC system transfer function acting on the scalar signals, by

providing and analytical formulation of the partial transfer function due to the individual

sources of attenuation (equations in Appendix A of Moncrieff et al., 1997). In

ECO2S::Fluxes these are recalculated at each run, to account for current parameters (e.g.

average wind speed). The overall transfer function is then derived as the product (in the

frequency space) of the individual ones (Eq. 11). This transfer function is applied to

49

analytical scalar flux cospectra (Eqs. 12-18, a reformulation after Kaimal et al., 1972), also

recalculated at each run, to account for atmospheric stratification. Correction factors are

finally derived, from carbon dioxide and water vapour fluxes, following Eq. 10 in

(Moncrieff et al., 1997). This correction method does not need any extra input, as all

functions can be evaluated starting from eddy standard data.

Horst (1997): Assuming a cospectral shape for scalar fluxes (Eq. 6), Horst derived an

analytical expression for the spectral attenuation (Eq. 11), with parameters depending on the

atmospheric stability regime ( , mn ), as well as on the EC system characteristics as a low-

pass filter ( c ). Note that Eq. 5 in (Horst, 1997) is equal to Eq. 3 in (Ibrom et al., 2007a),

with 12 cc f . Thus, the cut-off frequencies calculated with ECO2S::Spectra (RH-

dependent for water vapour, time-dependent for carbon dioxide), can be used to calculate c

and apply the Horst’s correction. Accordingly, when selecting this option, the GUI turns on

two extra mandatory entries, namely the Transfer function parameters file and the Cut-off

frequency vs. RH file, both of them created by ECO2S::Spectra. These files have the name

patterns: eco2s_ID_IIR_params.txt and eco2s_ID_cutoff_vs_rh.txt and can be found in the

main output directory selected when running ECO2S::Spectra.

Ibrom et al. (2007): this is a fully in-situ method. It only assumes a predefined shape for the

system transfer function (identical to the one assumed by Horst), that is adapted to the

current case with the procedure described at p. General Options Tab37. The method requires

the parameterization of a model (Eq. 9 in Ibrom et al., 2007a) for the H2O/CO2 correction

factor, as a function of atmospheric stability, wind speed and cut-off frequency. The

parameterization is performed in ECO2S::Fluxes and needs an extra input file, an

intermediate file created by ECO2S::RawProcess, the “degraded temperatures w-

covariances” file, whose name pattern is: eco2s_ID_vdegT_cov.csv. This file contains a

simulation of the effect of low-pass filtering, performed starting from sonic temperature

time series (taken as a proxy for unaffected scalar turbulent series) and applying the “Infinite

Impulse Response” filter with different cut-off frequencies. Please refer to the original

publication for details on the procedure and its theoretical background. Selecting this

options, the GUI forces you to enter three extra files: the Transfer function parameters file,

the Cut-off frequency vs. RH file and the Degraded temperatures w-covariances file

ECO2S I: this method, also based on (Ibrom et al., 2007a), differ from the previous one in

that the correction factors are not calculated from a model, rather they are derived by

50

applying the raw-file-specific transfer functions to the full (i.e., not binned) raw-file-specific

cospectrum of swT . Thus, this option requires that in ECO2S::RawProcess the option to

Output full wT-cospectra (p. 23) , was checked and the GUI forces you to select the

directory where such cospectra have been stored. Furthermore, also in this case the Transfer

function parameters file and the Cut-off frequency vs. RH file must be entered. Finally, this

method allows for a further refinement: checking the option Add analytical portion of TF to

in-situ ones, will cause ECO2S to add the partial analytical transfer functions of (Moncrieff

et al., 1997) that describe the high-frequency losses inherent in the anemometer’s

measurement of temperature spectra. This can be done to account for the fact that the

measured sonic temperature spectrum, assumed as a reference, is actually attenuated at the

high-frequency end from the finite time-space resolution of the anemometer.

Custom: this method, still in “alpha” version, is intended to allow you to build up your

spectral correction procedure, by combining different options. Because the method is still

highly unstable, it is not described here in details. However, you may attempt to select

“reasonable” options from the GUI, and see the results (and possibly report us any bugs!).

High-pass filtering correction

Checking this option will instruct ECO2S::Fluxes to apply a correction for the low-frequency

attenuation implied by the detrending procedure. ECO2S applies (the inverse of) a transfer function

that depends on the detrending method. Analytical formulations for the method supported in

ECO2S are described, for example, in (Rannik and Vesala, 1999). The information about the

selected detrending method is silently passed from ECO2S::RawProcess to ECO2S::Fluxes.

51

Post-processing Options Tab

In this tab you can select further processing, beyond the calculation of corrected fluxes. Currently,

ECO2S allows the calculation of quality flags for the fluxes and the estimation of the flux footprint.

Quality check

Check this option if you want ECO2S::Fluxes to calculate and output quality flags for sensible heat,

water vapour and CO2 fluxes. Quality flags are calculated following (Foken et al., 2004). For each

averaging period, the procedure involves the execution of two tests - for which individual flags are

calculated - and the combination of such flags into a summary flag, that is the one you will find

beside each flux in the output files. The steady state test (Foken and Wichura, 1996) compares the

statistical parameters determined for the flux averaging period and for short intervals within this

period. The turbulence development test, also described in (Foken and Wichura, 1996), assesses the

turbulent conditions by analyzing the measured integral turbulence characteristics as a function of

the atmospheric stratification and comparing them with a model proposed by (Foken et al., 1991).

In ECO2S, the steady state test is performed by ECO2S::RawProcess, while the turbulence

development test is performed here in ECO2S::Fluxes. Thus, checking this option requires that you

select the file containing the results of the steady state test in the Quality check auxiliary file entry.

This file is stored in the \eco2s_aux subfolder created by ECO2S::RawProcess in its main output

folder and has a name pattern like: eco2s_ID_qc_test.csv, with ID being the identifier of the current

processing project. You shall find the proper file path already pre-compiled by the GUI at the

successful end of the ECO2S::RawProcess run.

52

The overall flag can be calculated according to two different schemes:

FLUXNET standard (0/1/2): refers to the standard of the FLUXNET database, where the

value “0” means high quality, “1” means poorer quality, but still acceptable for derivation of

annual budgets and “2” suggests to discard the related flux.

Foken et al. (2004): refers to a different flagging policy, described in (Foken et al., 2004),

that ranks fluxes on a scale from “1”, top quality, to “9” poorer quality.

Footprint estimation

Currently, ECO2S supports two methods for estimating flux footprint. Both methods are one-

dimensional simple parameterizations and the (cross-wind integrated) footprint estimation is

provided as the (upwind) distances from the EC system contributing 70 and 95% to total fluxes,

plus the peak-contribution distance.

Schuepp et al. 1990: This footprint model, described in (Schuepp et al., 1990), is based on

an analytic solution of the advection-diffusion equation of a scalar in the turbulent boundary

layer (Gash, 1986) and provides a tool for estimating the footprint in neutral and unstable

stratifications, based on the friction velocity, the roughness length and the zero-plane

displacement height. To be completed.

Kljun et al. 2004: the footprint parameterization described in (Kljun et al., 2004) is based

on a scaling procedure for the flux footprint function, parameterised against footprint

simulations performed with a Lagrangian stochastic model. The parameterisation was

proved to be universally valid (given the value of the roughness length) to a large degree of

accurateness, within the limits explained in the referenced paper (Sect. 3.4), and in a very

wide range of atmospheric stratifications and EC systems heights. In ECO2S::Fluxes, the

footprint estimation is performed following (Kljun et al., 2004, Eq. 7), with parameters set

according their Eqs. 13-16 and using the roughness length available from the time-varying

info file (see p. 44), or from the ECO2S::Datalogging project file. As explained by the

authors, the estimation of the peak distance provided by the parameterisation is closely

similar to the one provided by the full model, while at higher percentages (such as 70% and

especially 95%) the accurateness is slightly reduced, also due to the flatness of the footprint

function at the far limit. The footprint model, however, is not valid for low friction

velocities, thus for 1

* 2.0 msu the footprint is not estimated and ECO2S::Fluxes reports

an error code on output.

53

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