ARM TR-048

> Carbon Dioxide Flux Measurement Systems (CO~2~FLX) Handbook
>
> January 2004
>
> M.L. Fischer
>
> Work supported by the U.S. Department of Energy,
>
> Office of Science, Office of Biological and Environmental Research

# Contents {#contents .Heading-Front}

[1. General Overview 1](#general-overview)

[2. Contacts 1](#contacts)

[3. Deployment Locations and History
2](#deployment-locations-and-history)

[4. Near-Real-Time Data Plots 2](#near-real-time-data-plots)

[5. Data Description and Examples 2](#data-description-and-examples)

[6. Data Quality 6](#__RefHeading___Toc94680407)

[7. Instrument Details 8](#instrument-details)

**Tables**

[Table 1. 5](#__RefHeading___Toc94680443)

[Table 2. 9](#__RefHeading___Toc94680444)

# General Overview

The Southern Great Plains (SGP) carbon dioxide flux (CO~2~ flux)
measurement systems provide half-hour average fluxes of CO~2~, H~2~O
(latent heat), and sensible heat. The fluxes are obtained by the eddy
covariance technique, which computes the flux as the mean product of the
vertical wind component with CO~2~ and H~2~O densities, or estimated
virtual temperature. A three-dimensional sonic anemometer is used to
obtain the orthogonal wind components and the virtual (sonic)
temperature. An infrared gas analyzer is used to obtain the CO~2~ and
H~2~O densities. A separate sub-system also collects half-hour average
measures of meteorological and soil variables from separate 4-m towers.

# Contacts

## Mentor

Marc L. Fischer, Staff Scientist

Atmospheric Sciences Department\
Environmental Energy Technologies Division\
Mail Stop 51-208\
E.O. Lawrence Berkeley National Laboratory\
1 Cyclotron Rd.\
Berkeley, CA 94720

Phone: (510) 486-5539\
Fax: (510) 486-5298\
email: <mlfischer@lbl.gov>\
web page: <http://eetd.lbl.gov/env/mlf/>

## Instrument Developer

David P. Billesbach, Research Professor

206 L.W. Chase Hall\
University of Nebraska\
Lincoln, NE 68583

Phone: (402) 472-7961 \
email: <dbillesbach1@unl.edu>

For instrument repair and maintenance:

Gill Solent, UK\
US Dist. Texas Electronics\
Phone: (800) 424-5651\
Website: <http://www.gill.co.uk/>

Licor Environmental\
Lincoln, Nebraska\
Phone: (800) 447-3576

Website: <http://env.licor.com/>

Campbell Scientific\
Logan, Utah\
Phone: (435) 753-2342\
Website: <http://www.campbellsci.com/>

# Deployment Locations and History 

The number and location of the sensors on the SGP 60-m tower has changed
over time; the following changes have been made:

September 2000. Initial installation of one system on the southeast boom
at 60 m on the Central Facility (CF) tower.

December 2002. First system removed from southeast boom. Systems
installed on the 25- and 60-m west booms on the CF tower. Combined eddy
covariance system at 4.5-m and supporting 4-m meteorological measurement
tower installed near base of 60-m tower.

# Near-Real-Time Data Plots

See data quicklooks from yesterday at:

-   [yest60m](http://co2anal.lbl.gov/worldview/yest60m.html)

-   [yest25m](http://co2anal.lbl.gov/worldview/yest25m.html)

-   [yest4m](http://co2anal.lbl.gov/worldview/yest4m.html)

# Data Description and Examples

## Data File Contents

The data are presented in three levels of processing: a1, b1, and b1met.
Each level of processing has an accordingly named directory. For more
detailed information on processing, please see [Data Processing
Algorithms](http://www.arm.gov/instruments/static/co2flx.stm#Data_User_Notes%23Data_User_Notes)
section. In summary:\
\
Directory 'a1': sgp30p1flxT1.a1.YYYYMMDD.000000.cdf\
    First level of processing where raw data are converted to physical
units, despiked, lag is corrected, statistics are calculated, etc.
"YYYYMMDD" denotes year, month, day of the file. All data are in cdf
format.

Directory 'b1': sgp30p1flxT1.b1.YYYYMMDD.000000.cdf\
    Second level of processing where data are quality checked and
corrections applied properly rotated.

Directory 'b1met': sgp30p1flxmetT1.b1.YYYYMMDD.000000.cdf\
    Third level of processing where other meteorological data are added
to the b1 level of processing

### Primary Variables and Expected Uncertainty

The CO~2~ flux systems measurement systems provide from ½- to 4-hour
mean estimates of the fluxes of CO~2~, H~2~O (latent heat), and sensible
heat from a variable area (footprint) of the land surface upwind of the
instrument. In rough terms, the extent of the footprint, which depends
on the mean wind speed and the degree of turbulent mixing in the
atmosphere, varies from 5-100 times the height of the sensors above the
land surface. For example, the instrument located at 60 m on the CF
tower detect land surface fluxes at distances between approximately
0.3-6 km from the tower depending on meteorological conditions.

The fluxes are computed from the following directly measured data. The
sonic anemometer at 10 Hz CO~2~ meausres orthogonal components of the
wind velocity, u, v, and w (m s^-1^), and sonic temperature (K), which
is approximately equal to virtual temperature. An infrared gas analyzer
(IRGA) measures H~2~O densities (mmol m^-3^).

#### Definition of Uncertainty

Uncertainties in the measurements obtained under well-mixed conditions
are typically dominated by random noise from atmospheric turbulence and
the instrument. The most common source of uncertainy at night is caused
by imperfect mixing under low turbulence conditions. A third source of
uncertainty is noise caused by airborne material (e.g., rain) that
briefly obscures the sound or light path of the sensors. The data
processing software is designed to provide diagnostic variables to
identify the sources of uncertainty that affect the measurements. See
the description of processing algorithms given below.

Under normal operation, the instrument noise limits to flux measurements
are as follows:\
CO~2~ flux: detection limit \~ 0.1 umol/m\^2/s, gain uncertainty 1-3%\
H~2~O flux: detection limit \~ 10 W/m\^2/s, gain uncertainty 1-3%\
Sensible heat: detection limit \~ 10 W/m\^2/s, gain uncertainty 1-3%

### Secondary/Underlying Variables

Secondary variables are provided for assessing the state of the
atmosphere including: friction velocity and Monin-Obukhov scale length;
radiatiative balance and surface reflectivity variables including upward
and downward shortwave, longwave, and photosynthetically active
radiation; and soil variables including soil temperature and moisture.

### Diagnostic Variables

Additional diagnostic variables include the first four statistical
moments and spike counts (see below) of wind velocity, CO~2~ and H~2~O
vapor densities, and virtual temperature.

### Data Quality Flags

Output files include QC flags as described below:

***Raw data Quality Assurance (QA)/QC***

Spike count for u,v,w,T, q, c

This is a summary of the QC flags in a1 and b1 files.

\*\*\*\*\*\*Flags present in \_a1\_ files:

nspk_unrot_u number of samples out of range u

speed \> 40m/s\
deviation from mean \> 6\*(std dev)

nspk_unrot_v number of samples out of range v

speed \> 40m/s\
deviation from mean \> 6\*(std dev)

nspk_unrot_w number of samples out of range w

> speed \> 40m/s\
> deviation from mean \> 6\*(std dev)

nspk_t number of samples out of range t

deviation from mean \> 5\*(std dev)

nspk_q number of samples out of range q

> value \> 2000 mmol/m^-3^\
> value \< 0 mmol/m^-3^\
> deviation from mean \> 6\*(std dev)

nspk_c number of samples out of range c

> value \> 30 mmol/m^-3^\
> value \< 10 mmol/m^-3^\
> deviation from mean \> 6\*(std dev)

***Processed Data Checks***

\*\*\*\*\*\*Flag Scheme in b1 level files:

Almost every variable \'x\' has a quality control flag named \'qc_x\'.
In general, the values of QC flags are as follows:

[]{#__RefHeading___Toc94680443 .anchor}Table 1.

  ----------------------------------- -----------------------------------
  **qc value**                        **relevant condition**

  0                                   value not suspect

  1                                   value missing

  2                                   value below minimun or above
                                      maximum or value is +-infinity

  4                                   one or more dependencies failed;
                                      see the "dependency" attribute of
                                      variable; if a dependency is a
                                      spike count, it fails if it is
                                      \>100, if a dependency is a
                                      variable, it fails when the
                                      variable's qc flag is not equal to
                                      0.

  8                                   value has large variance; see
                                      "large variance condition"
                                      attribute of variable

  16                                  value suspect because variable has
                                      more than 100 spikes; these spikes
                                      are counted in a1 level data; see
                                      "dependencies" attribute of
                                      variable; currently this flag
                                      applies to t, q, c.

  32                                  value suspect because of another
                                      condition, see "special condition"
                                      attribute of variable. Currently
                                      only applies to fc_corr, wc_2d,
                                      ustar.
  ----------------------------------- -----------------------------------

For more specific minimum, maximum, and other values, please see the
[Data Description
File](http://www.arm.gov/instruments/publications/co2flx-data-format.html).

### Dimension Variables

Each variable has dimensions included in the data files.

## Annotated Examples

The variable for CO~2~ flux is fc_corr (μmol CO~2~ m^-2^ s^-1^). Typical
daytime values are --30 \< fc_corr \< 10 (μmol CO~2~ m^-2^ s^-1^). The
corresponding quality control variable is qc_fc_corr (dimensionless)
which normall has a value of zero. Low turbulence at night is identified
as occurring when the mean wind speed is less than 2 m s^-1^.

## User Notes and Known Problems

The instruments have provided high quality data for a large fraction
(\>80%) of their operating lifetime. Occassional loss of data has
occurred due to loss of power communications or instrument malfunction.
Also, the operation of some of the auxiallary sensors (particularly the
soil measurement instruments) has been optimized over time. All data
users are strongly urged to review the quality reports describing
intermittent problems and changes to sensors and the data processing,
then refer further questions to the instrument mentor.

## Frequently Asked Questions

***Where do I get more information?***

Contact the instrument mentor at <mlfischer@lbl.gov>.

# Data Quality

## Data Quality Health and Status

Data quality is evaluated by inspecting Quality Control (QC) flags and
variables in processed data.

**Data Processing Algorithms**

The first program processes the raw (a0) data to produce intermediate
(a1) data files. The averaging time for calculations can be varied to
produce equipment center (EC) average values for each ½ hour (other
averaging times can be requested of 1, 2, and 4 hr). The calculation is
performed as follows:

From a0 to a1:

1.  Read in raw data and convert to physical units (u,v,w \[m/s\], T
    sonic \[C\], CO~2~ and H~2~0 \[mmol/m^‑3^\]).

2.  Shift the CO~2~ and H~2~0 signals back by (2 - 3 samples) to correct
    for a fixed time lag in the LI‑7500 analyzer.

Identify and remove spikes from data using 100-second running mean
filter. Spikes are identified as data points with values more than a set
number of standard deviations away from running mean. Spike data are
given value of running mean and are not used to update mean. Spikes are
counted and the mean value of the spikes is calculated.

3.  Calculate statistics (mean, variance, skewness, and kurtosis) of
    each variable and covariances between all signal pairs.

4.  Calculate 2-D coordinate rotation to zero mean w and v and apply to
    vector and covariance quantities.

5.  Write out results.

From a1 to b1: processes intermediate (a1) files to produce estimates of
turbulent fluxes with initial QC flags as follows:

1.  Compute turbulent fluxes of CO~2~ and H~2~O including appropriate
    Webb-Pearmann-Leuning corrections (Webb et al, 1980) for sensible
    and latent heat (Webb et al, 1980).  

```{=html}
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```
6.  Inspect and flag data falling outside of acceptable limits based on
    variance, spike counts, and turbulence conditions u\*.

7.  Write out results.

From b1 to metb1:

1.  For the 4-m systems, merge meteorological data with b1 data file.

**Eddy Covariance Calculations**

The algorithm that computes the turbulent fluxes (a1tob1) for the data
collected at 4 m uses the air temperature, pressure, and relative
humidity from meteorological sensors to calculate the density and
specific heat. However, at present, the 25 and 60 m systems use the
virtual temperature measured by the anemometer and the H~2~O density
measured by the IRGA to estimate air density and specific heat, assuming
a constant pressure of 98 kPa. This will cause a small errors in cases
where pressure or temperature are slightly different from the measured
values.

No corrections are made for loss of spectral energy due to sensor
separation. Using the work of Moore (1986), we have estimated these
corrections to be in the range of 3-7% for most conditions at 4 m above
the crops, but it is unlikely to be significant for the measurements at
25 and 60 m.  

The fluxes only reflect turbulent fluxes and do not include corrections
for storage of CO~2~, H~2~O, or heat in the air between the sensor and
the land surface. Although this is unlikely to be an important
correction for the 4-m system, this correction is often significant for
the 60-m system. We are working to incorporate data from a precision gas
system to include a storage correction for the 25- and 60-m heights.

**Soil Temperature and Moisture**

Soil temperature sensors were installed at the following depths:

T1, T4 = 25 cm; T2, T5= 15 cm; T3, T6 = 5 cm

Soil moisture sensors were installed at the following times:

July 2001: M1, M3, M5, M7 = 15 cm; M2, M4, M6, M8 = 5 cm

December 2002- present: M1, M3, M5, M7 = 25 cm; M2, M4, M6, M8 = 5 cm

A large temperature sensitivity was observed in the soil moisture
sensors exhibit. This is evident in sensors located in shallow soil with
large temperature variations. This has not been corrected by processing
algorithm to date. This correction will be included in future files.
People interested in performing their own corrections may want to
consider using the diurnal soil temperature variations to diurnal
variations in moisture signals.

## Data Reviews by Instrument Mentor

Visual QC frequency: daily to weekly

QC delay: typically 1-2 days

QC type: - 

Instrument mentor Marc Fischer and data processing assistant Igor
Pesenson routinely view graphical displays produced at Lawrence Berkeley
National Laboratory (LBNL). The displays include graphs of CO~2~, H~2~O,
sensible fluxes, mean and variance of CO~2~ concentration (not corrected
for barometric pressure) and wind speed.

## Data Assessments by Site Scientist/Data Quality (DQ) Office

All DQ Office and most Site Scientist techniques for checking have been
incorporated within [DQ HandS](http://dq.arm.gov/) and can be viewed
there.

## Value-Added Procedures and Quality Measurement Experiments

None at present. A gap-filled data file is being developed.

# Instrument Details

## Detailed Description

### List of Components

Components for Eddy Covariance Calculations:

-   3-D Sonic Anemometer, Gill Solent Windmaster Pro

> Orthogonal wind velocities u, v, and w\
> Range: ± 20 m/s\
> Accuracy: u,v =1.5% root mean square (RMS) error, w =3% RMS error\
> Resolution: 0.01 m/s

-   Sonic temperature (from speed of sound (SOS))\
    Range: -40 to +60 deg C (307-367 m s-1)\
    Accuracy: 3% RMS error in SOS\
    Resolution: 0.02 deg C

Infrared Gas Analyzer, Licor Inc. LI-7500 (see
[http://env.licor.com/](http://www.decagon.com/echo/))

-   CO~2~ density\
    Range: 0 to 110 mmol/m^3^;\
    Accuracy: \~ 1% (limited by calibration procedure)\
    Precision: \~ 4 umol/m^3^ (typical RMS instrument noise)

-   H20 density\
    Range: 0 to 2000 mmol m^-3^\
    Accuracy: \~ 1% (limited by calibration)\
    Precision: 0.14 mmol/m^3^ (typical RMS instrument noise)

Data collection system

-   266 - 600 MHz PC clone

-   Data collection software:\
    \~ 9/11/2000 - 12/19/2001.  Data collection performed with
    gillsonic.c running under MS Windows NT (written in C Programming
    language for MS-DOS at NOAA-ATDD by Tilden Meyers and modified for
    use at ARM).

12/20/2001 - 12/19/2002.  Data collection performed with WinfluxWMP.cpp
software running under MS Windows NT (written in C++ by Joe Verfaillie
at CSU San Diego). 

12/19/2002 - present.  Data collection performed with sonic-irga.c
software running under Redhat 7.3 (written in C by Ed Dumas at
NOAA-ATDD).  Note that the data collection system also collects and
stores digital serial data from the IRGA.

[]{#__RefHeading___Toc94680444 .anchor}Table 2.

Components for Meteorological and Soil Measurements Included in 4-m Data
Sets**:**

  --------------------------------- ----------------------------------------
  Variable measured                 Instrument

  Mean horizontal wind speed and    [Climatronics CS800-12 wind
  direction                         set](http://www.campbellsci.com/)

  Temperature and relative humidity [Vaisala Humiter 50Y  (2, 3
  profiles                          m)](http://www.vaisala.com/)

  Mean atmospheric pressure         [Vaisala PTB101B
                                    barometer](http://www.vaisala.com/)

  Soil heat flux                    [REBS HFT3 soil heat flux plates 
                                    (4)](http://www.campbellsci.com/)

  Soil temperature profiles         Type E thermocouples  (6)

  Soil moisture profiles            [Decagon ECHO soil moisture sensors
                                    (8)](http://www.decagon.com/echo/)

  Photosynthetically Active         [LiCor LI-190SA quantum
  Radiation                         sensor](http://env.licor.com/)

  Downwelling Short Wave Radiation  [LiCor LI-200SA
  (0.4-11 microns)                  pyranometer](http://env.licor.com/)

  Upwelling and downwelling         [Kipp & Zonen CNR-1
  radiation (0.3 mm -- 2.8 mm and 5 radiometer](http://www.kippzonen.com/)
  mm -- 50 mm)                      

  Net radiation                     [Kipp & Zonen NR-lite net
                                    radiometer](http://www.kippzonen.com/)

  Summed precipitation              [Texas Instruments TE525 tipping bucket
                                    rain gage](http://www.campbellsci.com/)

  Data Logger                       [Campbell CR23x (some systems have
                                    CR10x)](http://www.campbellsci.com/)
  --------------------------------- ----------------------------------------

### System Configuration and Measurement Methods

Pairs of anemometers and IRGAs are located on and near the CF 60-m
tower. Data from the anemometer are transmitted to a personal computer
(PC) in an instrument shed at the base of the tower. The PC collects and
stores the serial binary data stream from the sonic anemometer and IRGA
(for more details, see data collection system notes below).  The raw
data are transferred to LBNL, processed into the ARM Archive format, and
inspected for problems on a daily basis. Processed files are sent to the
ARM Archive using the Site Transfer Suite on a weekly basis.

### Specifications

This section is not applicable to this instrument.

## Theory of Operation

Turbulent fluxes are calculated using standard methods in
biometeorology. See Section 7.7, Citable References for discussions.

The 3-D sonic anemometer uses three pairs of orthogonal ultrasonic
transmit/receive transducers to measure the transit time of sound
signals traveling between the transducer pairs. The wind speed along
each transducer axis is determined from the difference in transit times.
The sonic temperature is computed from the speed of sound, which is
determined from the average transit time along the vertical axis. A pair
of measurements are made along each axis 100 times per second. Ten
measurements are averaged to produce 10 wind measurements along each
axis and 10 temperatures each second.

The IRGA measures CO~2~ and H~2~O densities by detecting the absorption
of infrared radiation by water vapor in the light path. Details of the
IRGA operation and performance can be obtained from Licor Env. Inc.
(<http://env.licor.com/PDF_Files/LI7500.pdf>).

Data are collected on a standard personal computer. Data are collected
in ½-hour intervals, using the computer clock start as a time reference.
Each ½-hour data file has a timestamp reflecting the start time of the
file. The computer clock is updated on a regular basis using time server
software. The daily collection of 48 raw data files are downloaded from
the data collection computer to a processing computer at the LBNL on a
daily basis and reduced to produce eddy covariance estimates of
turbulent fluxes. A set of data processing algorithms are used to create
files suitable for inspection and ingest into the ARM data archive.

## Calibration

This section is not applicable to this instrument.

### Theory

The sonic anemometer does not require maintenance or calibration. The
IRGA offset and gain need to be calibrated on a periodic basis. The IRGA
is calibrated by introducing gas of know concentration into a
calibration hood that surrounds the light path over which infrared
absorption is measured. The offset is typically calibrated using dry
N~2~ from a gas bottle. The gain of the CO~2~ and H~2~O channels are
calibrated using a bottle with a known concentration of CO~2~ and flow
from a H~2~O vapor generator (e.g. Licor Inc. LI-610 Dew Point
Generator).

### Procedures

This section is not applicable to this instrument.

### History

The system in longest continuous operation is the system at 60 m on the
60-m tower.  The calibration interval for that system is:

October, 18, 2000\
July, 13, 2001\
December, 18, 2001\
December, 20, 2002; replaced.

The portable flux systems are calibrated before each portable deployment
period.

## Operation and Maintenance

The sonic anemometer does not require maintenance or calibration. The
IRGA offset and gain are calibrated on a periodic basis following the
manufacturers recommended procedure.

### User Manual

This section is not applicable to this instrument.

### Routine and Corrective Maintenance Documentation

This section is not applicable to this instrument.

### Software Documentation

General description of the data product formats can be found in the
[Data Description
File](http://www.arm.gov/instruments/publications/co2flx-data-format.html).

### Additional Documentation

This section is not applicable to this instrument.

## Glossary

Also see the [ARM Glossary](http://www.arm.gov/about/glossary.stm).

## Acronyms

CF: Central Facility

DQ: Data Quality

EC: equipment center

IRGA: infrared gas analizer

LBNL: Lawrence Berkeley National Laboratory

PC: personal computer

RMS: root mean square

SGP: Southern Great Plains

SOS: sound of speed

QA: Quality Assurance

QC: Quality Control

Also see the [ARM Acronyms and
Abbreviations](http://www.arm.gov/about/acronyms.stm).

## Citable References

Kaimal, J.C., Finnigan, J.J., 1994. Atmospheric Boundary Layer Flows:
Their Structure and Measurement. Oxford University Press, New York

Moore, C.J., 1986. Frequency Response Corrections for Eddy Correlation
Systems. Boundary-Layer Meteorol. 37, 17-35

Paw U, K.T., Baldocchi, D.D., Meyers, T.P., Wilson, K.B., Correction of
Eddy-Covariance Measurements Incorporating Both Advective Effects and
Density Fluxes. Boundary-Layer Meteorol. 97,487-511

Webb, E.K., Pearman, G.I., and Leuning, R., 1980. Correction of Flux
Measurements for Density Effects due to Heat and Water Vapour Transfer.
Quart. J. Roy. Meteorol. Soc. 106, 85-100