DOE/SC-ARM-TR-037

> Energy Balance Bowen Ratio (EBBR) Handbook
>
> January 2007
>
> D.R. Cook
>
> 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
1](#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 12](#data-quality)

[7 Instrument Details 16](#instrument-details)

**Figures**

[1 Plot showing sensible and latent heat fluxes showing a normal diurnal
variation in heat fluxes. 5](#__RefHeading___Toc119730796)

[2 Plot showing the spiked data replaced by the BA EBBR VAP with fluxes
calculated\
with the bulk aerodynamic technique. 6](#__RefHeading___Toc119730797)

**Tables**

[1 EBBR status 1](#__RefHeading___Toc119731894)

# General Overview

The energy balance Bowen ratio (EBBR) system produces 30-minute
estimates of the vertical fluxes of sensible and latent heat at the
local surface. Flux estimates are calculated from observations of net
radiation, soil surface heat flux, and the vertical gradients of
temperature and relative humidity (RH). Meteorological data collected by
the EBBR are used to calculate bulk aerodynamic fluxes, which are used
in the Bulk Aerodynamic Technique (BA) EBBR value-added product (VAP) to
replace sunrise and sunset spikes in the flux data. A unique aspect of
the system is the automatic exchange mechanism (AEM), which helps to
reduce errors from instrument offset drift.

# Contacts

## Mentor

David R. Cook

Environmental Research Division

Argonne National Laboratory, Bldg. 203

Argonne, Illinois 60439

Phone: 630-252-5840

Fax: 630-252-5498

[drcook@anl.gov](mailto:jcliljegren@anl.gov)

## Instrument Developer

Radiation and Energy Balance Systems, Inc.

P.O. Box 15512

Seattle, Washington 98115-0512

Phone: 206-624-7221

Fax: 425-228-4067

Contact person is Charles Fritschen

<rebsinc@earthlink.net>

# Deployment Locations and History 

  --------------------------------- ------------------- -------------- ------------ -------------
  []{#__RefHeading___Toc119731894                                                   
  .anchor}**Table 1**. EBBR status                                                  

  **Extended Facility**             **Facility          **Date         **Date       **Status**
                                    Location**          Installed**    Removed**    

  2                                 Hillsboro, KS       1997/05/23                  Operational

  4                                 Plevna, KS          1993/04/03                  Operational

  7                                 Elk Falls, KS       1993/08/29                  Operational

  8                                 Coldwater, KS       1992/12/08                  Operational

  9                                 Ashton, KS          1992/12/10                  Operational

  12                                Pawhuska, OK        1993/08/29                  Operational

  13                                Lamont, OK (at the  1992/09/14                  Operational
                                    Central Facility                                
  --------------------------------- ------------------- -------------- ------------ -------------

  ------------ ------------------- -------------- ------------ -------------
  **Table 1**.                                                 
  (cont'd)                                                     

  **Extended   **Facility          **Date         **Date       **Status**
  Facility**   Location**          Installed**    Removed**    

  15           Ringwood, OK        1992/09/16                  Operational

  18           Morris, OK          1997/09/10                  Operational

  19           El Reno, OK         1997/05/29                  Operational

  20           Meeker, OK          1993/04/05                  Operational

  22           Cordell, OK         1993/04/05                  Operational

  25           Seminole, OK        1997/10/22     2002/04/08   facility
                                                               vacated

  26           Cement, OK          1992/06/10                  Operational

  27           Earlsboro, OK       2003/05/02                  Operational
  ------------ ------------------- -------------- ------------ -------------

# Near-Real-Time Data Plots

To view near-real-time plots of EBBR data, visit the NCVweb at
<http://dq.arm.gov/ncvweb/ncvweb.cgi>. Choose "sgp" from the menu, and
click the "Submit Site" button. Then choose sgp30ebbrE##.b1 from the
next menu (## stands for extended facility number) and click the "Submit
DataStream" button. Now highlight a date or range of dates for which you
are interested in seeing EBBR data and click on the "Plot File" button.
Choose a variable for the Y axis and click on the "Apply Changes" button
to plot the data. Time series and multiple plots can also be created.

# Data Description and Examples

## Data File Contents

### Primary Variables and Expected Uncertainty

**30 minutes**:

Sensible Heat Flux (h): 10% uncertainty

Latent Heat Flux (e): 10% uncertainty

Net Radiation (q): 5% uncertainty

Average Soil Surface Heat Flux (ave_shf): 10% uncertainty

#### Definition of Uncertainty

We define uncertainty as the range of probable maximum deviation of a
measured value from the true value within a 95% confidence interval.
Given a bias (mean) error *B* and uncorrelated random errors
characterized by a variance *σ^2^*, the root-mean-square error (RMSE) is
defined as the vector sum of these,

$\text{RMSE} = \left( B^{2} + s^{2} \right)^{\frac{1}{2}}$.

(*B* may be generalized to be the sum of the various contributors to the
bias and *σ^2^* the sum of the variances of the contributors to the
random errors). To determine the 95% confidence interval, we use the
Student's *t* distribution: *t*~n;0.025~ ≈ 2, assuming the RMSE was
computed for a reasonably large ensemble. Then the *uncertainty* is
calculated as twice the RMSE.

### Secondary/Underlying Variables

**30 minutes**:

tair_top

tair_bot

thum_top

thum_bot

hum_top

hum_bot

vp_top

vp_bot

pres

sm1, sm2, sm3, sm4, sm5

ts1, ts2, ts3, ts4, ts5

shf1, shf2, shf3, shf4, shf5

c_shf1, c_shf2, c_shf3, c_shf4, c_shf5

cs1, cs2, cs3, cs4, cs5

ces1, ces2, ces3, ces4, ces5

g1, g2, g3, g4, g5

bowen

wind_s

res_ws

wind_d

**15 minutes**:

rr_tref

rr_thum_r

rr_thum_l

rr_ts1, rr_ts2, rr_ts3, rr_ts4, rr_ts5

r_sm1, r_sm2, r_sm3, r_sm4, r_sm5

mv_hum_r

mv_hum_l

mv_pres

mv_q

mv_wind_d

mv_home

mv_hft1, mv_hft2, mv_hft3, mv_hft4, mv_hft5

tair_r

tair_l

wind_s

**5 minutes**:

tref

tair_top

tair_bot

thum_top

thum_bot

hum_top

hum_bot

vp_top

vp_bot

q

pres

wind_s

res_ws

wind_d

### Diagnostic Variables

**30 minutes**:

tref

sigma_wd

hom_15

hom_30

**15 minute**:

bat

signature

**5 minute**:

sigma_wd

home

### Data Quality Flags

**30 minutes**:

qcmin1-24

qcmax1-24

qcdelta1-24

qcmin25-48

qcmax25-48

qcdelta25-48

qcmin49-72

qcmax49-72

qcdelta49-72

**15 minutes**:

qcmin1-24

qcmax1-24

qcdelta1-24

qcmin25-48

qcmax25-48

qcdelta25-48

### Dimension Variables

Note: lat, lon, and alt refer to the ground surface, not to the
instrument system height

**30, 15, and 5 minute**:

lat

lon

alt

base_time

time_offset

## Annotated Examples

The following plot of sensible (h) and latent (e) heat fluxes show a
normal diurnal variation in heat fluxes, with latent heat flux being
mostly negative during nighttime hours, as evaporation continues, and
sensible heat flux being positive. During daylight hours, both h and e
are negative, as energy is lost from the surface. The plot also shows
the spikes in the data that can occur at sunrise and sunset when the
Bowen ratio is near -1 (see the Bowen ratios annotated on the plot, near
the data spikes).

![](media/image1.png){width="4.857638888888889in"
height="3.192361111111111in"}

[]{#__RefHeading___Toc119730796 .anchor}Figure 1. Plot showing sensible
(h) and latent (e) heat fluxes showing a normal diurnal variation in
heat fluxes. Spikes in the data occur at sunrise and sunset when the
Bowen ratio is near -1.

The BA EBBR VAP replaces the spiked data with fluxes calculated with the
BA. The resultant combined flux data are shown in the next plot.

![](media/image2.png){width="5.216666666666667in"
height="3.3229166666666665in"}

[]{#__RefHeading___Toc119730797 .anchor} Figure 2. Plot showing the
spiked data replaced by the BA EBBR VAP with fluxes calculated with
the BA.

## User Notes and Known Problems

## Some conditions do not require Data Quality Reports (DQRs) because they occur somewhat frequently. These conditions include spikes in the sensible and latent heat fluxes when the Bowen ratio is near -1, short periods when the AEM is not functioning properly (this can be detected from the quality control \[QC\] checks in the data files), and short periods of missing data. {#some-conditions-do-not-require-data-quality-reports-dqrs-because-they-occur-somewhat-frequently.-these-conditions-include-spikes-in-the-sensible-and-latent-heat-fluxes-when-the-bowen-ratio-is-near--1-short-periods-when-the-aem-is-not-functioning-properly-this-can-be-detected-from-the-quality-control-qc-checks-in-the-data-files-and-short-periods-of-missing-data. .unnumbered}

Common instrumentation problems include the following:

-   condensation or frost on the net radiometer upper polyethylene dome
    (this can persist well into daylight hours)

-   net radiometer desiccant degradation

-   holes in the net radiometer top dome caused by bird claws (this can
    result in water in the net radiometer if the dome is not replaced
    before precipitation occurs)

-   soil sensors pulled from the ground or chewed by animals

-   a blown fuse in the AEM when the belt slides bind against the track

-   seized bearings in wind instruments

-   aging of sensors and electronic components

-   loosened electronic connections.

Preventative maintenance visits every two weeks and instrument mentor
quality assurance activities are designed to detect and correct these
problems to reduce the amount of incorrect data collected.

## Frequently Asked Questions

**How is the latent heat flux and sensible heat flux derived?**

The Bowen ratio technique is used to determine Bowen ratio, assuming
that the transfer coefficients of heat and water vapor are the same. The
Bowen ratio is then used in conjunction with net radiation and soil
surface heat flux measurements to determine sensible and latent heat
flux based on a budget approach. More details are provided in Section
7.2, Theory of Operation.

**What is the sign convention used for the energy flux densities?**

All energy flux densities have a positive sign when directed toward the
surface, and negative when directed away. For example, values of
sensible (h) and latent heat flux (e) could be 0 to -600 watts per meter
squared during the daytime in the summer.

**In the design of the EBBR stations, which data are considered the most
useful to Atmospheric Radiation Measurement (ARM) Science Team
members?**

The EBBR stations were designed primarily for computation of the
sensible and latent heat fluxes. The soil temperature, moisture, and
heat fluxes are measured in the upper 5 cm of the soil and therefore are
not very useful for determining root zone soil moisture and soil heat
flow. Other observations, such as air temperature, RH, atmospheric
pressure, and wind speed and direction are secondary measurements;
Surface Meteorology Observation Station (SMOS) measurements, where
available, should be used as the absolute measurements of these
quantities. For example, the EBBR atmospheric pressure data are not
measured with sufficient accuracy for many applications, whereas the
SMOS pressure data have a smaller uncertainty and might be suitable for
calculations of geostrophic winds. Other sources of reliable surface
meteorological data are available as external data for the ARM Program
from the Oklahoma Mesonet and from the Kansas network. The data user is
encouraged to use the data from the SMOS for such observations.

EBBR data are collected only at the Southern Great Plains (SGP) extended
facilities, including one at the Central Facility and some that are
collocated with boundary facilities, and where the local surface is not
tilled. Eddy correlation stations exist at nearly half of the extended
facilities to sample the latent heat, sensible heat, and momentum fluxes
above tilled cropland.

EBBR data can be used to compute momentum fluxes with a bulk aerodynamic
approach. This approach is used as the basis for the calculation of
sensible and latent heat fluxes by the BA EBBR VAP (Wesely et al. 1995).

**What do AEM home signals indicate?**

The AEM home signal outputs in the 5-, 15-, and 30-minute data streams
are in units of millivolts DC. The circuitry producing the millivolt
output is fairly rudimentary and therefore the millivolt value is
proportional to the DC voltage output of the EBBR power supply (solar/AC
charged battery). The home signal can therefore vary significantly
diurnally and can fall to unacceptable levels for the 15-minute value if
battery performance degrades too much.

During the first and third quarter hours, the right side (looking from
behind the AEM) aspirated radiation shield (housing temperature and RH
probes) is normally in the "bottom" (lowest elevation) position, and the
left side is in the "top" (greatest elevation) position. During this AEM
state, the 5-minute "home," 15‑minute "mv_home", and 30-minute "home_15"
values should be between 40 and 55.

During the second and fourth quarter hours, the left side (looking from
behind the AEM) aspirated radiation shield (housing temperature and RH
probes) is normally in the "bottom" (lowest elevation) position, and the
right side is in the "top" (greatest elevation) position. During this
AEM state, the 5‑minute "home," 15-minute "mv_home," and 30-minute
"home_30" values should be between 15 and 30.

**What soil measurements are made by the EBBR stations?**

Five soil heat flow sensors are located at a depth of 5 cm from the
surface, five long platinum resistance temperature detectors (PRTDs)
integrate the temperature from the surface to a depth of 5 cm, and five
soil moisture probes are located at a depth of 2.5 cm. Each set of five
soil sensors is averaged. Because soil is not horizontally homogeneous,
the sensors are spaced out in the soil locally to provide representative
samples.

The purpose of these sensors is to compute one term, the surface soil
heat flux. The soil temperature and moisture probes allow calculation of
energy storage in the layer of soil between the surface and the heat
flow plate depth of 5 cm. The soil moisture probes allow the soil heat
flow measurements to be adjusted for the conductivity of the soil.

The sensible and latent heat fluxes are computed by the EBBR data logger
with the standard energy balance equation, in which the surface soil
heat flux is usually a relatively small term. The surface soil heat flux
term cannot be precisely recalculated from the raw information because
of the way the soil energy storage term is computed with the EBBR data
logger, but, in principle, the raw information can be used to recompute
the sensible and latent heat fluxes with only a few percent error.

**If some of the soil probes are not working, can sensible and latent
heat fluxes be recalculated?**

Yes. The remaining working soil probe sets can be used to calculate an
average surface soil heat flux. See the procedure in Section 7.2, Theory
of Operation.

**What type of diurnal trends should appear in the EBBR data?**

Some examples of diurnal trends can be seen in various textbooks and
articles. For example, some data are shown in the special FIFE issue of
the *Journal of Geophysical Research* (Vol. 97, pp. 18,343-19,110),
e.g., the article by Fritschen et al. starting on p. 18,697 The ARM
Program uses a Fritschen-type EBBR station.

**What can be said about the quality of the EBBR data?**

The EBBR systems sometimes experience hardware problems. For example,
the AEM will sometimes malfunction. Some problems, like this one, can be
discerned by looking at the data quality flags.

The following information should be useful for interpretation of the
quality of data from the EBBR stations. Data quality flags should be
used to detect when the AEM is functioning properly. The rate of AEM
failure has been high at times. When it is not working, the estimates of
sensible and latent heat flux are unreliable and should not be used for
any scientific investigations, even if the flux estimates appear to be
reasonable.

To use the metadata on the AEM, the user should become familiar with the
field and global attributes described in a dump of the netCDF header.
The fields are defined there, and, in datasets recently provided, the
configuration of the data quality flags is briefly described at the end
of the list of the global attributes. The flags themselves are contained
in numbers at the end of the data listing. The next paragraph provides
some suggestions on the QC numbers (qcmin# and qcmax#) and the imbedded
flags relevant to the AEM.

QC flags in the standard, 30-minute data interval indicate when the AEM
is working for each half hour in the time series. The particular QC
flags of interest are the sixth and seventh bits of the 24-bit binary
numbers representing qcmin49-72 and qcmax49-72. The sixth bit of
qcmin49-72 is set to zero when the home_15 is greater than 35 mV, and to
unity when less. The sixth bit of qcmax49-72 is set to zero when the
home_15 is less than 70, and to unity when greater. A similar set of
criteria are applied to the seventh bit, but with a minimum of 15 and
maximum of 34.999999. Alternatively, if you choose not to convert the QC
numbers to binary form, you can inspect the values of home_15 and
home_30 to determine if they fall in the desired range. Because the
limit checks on the home signals were not properly set prior to
April 7, 1993, you must inspect home_15 and home_30, rather than qcmin#
and qcmax# for data collected prior to that date.

The QC flags should routinely be used for all of the variables. For some
variables, however, QC flags have not been set, and for some variables
(e.g., average soil heat flux \[ave_shf\], latent heat flux \[e\], and
sensible heat flux \[h\]) flags were not set until late May 1998, as is
evident in the listing of the field attributes. Nevertheless, some
information can be obtained by inspection of the data if you are
familiar with typical values. For example, Bowen ratios tend to be
positive during the day and negative at night. Daytime values are
usually between 0 and 2, and nighttime values can vary widely between
positive values and -50. A negative Bowen ratio during daylight hours
should be considered as possibly indicating suspect sensible and/or
latent heat flux values. During transition times lasting up to two half
hours near sunrise and sunset, the magnitude of the Bowen ratio can
sometimes be quite large, in which

case the sensible and latent heat flux values should be viewed as
suspect. Although no QC flags were set for latent and sensible heat
flux, values smaller than -1000 watts per meter squared and larger than
200 watts per meter squared are clearly suspect.

Routine checks reveal an expected offset drift of the RH probe of about
+2% per year caused by aging and dirt contamination of the RH sensing
element. This drift has also been observed in the Tower and SMOS RH
probes. Although this affects the absolute accuracy of the RH
measurement, it does not adversely affect the 30-minute vapor pressure
difference calculated from the RH and temperature measurements because
the RH probes drift at approximately the same rate and the AEM
exchanging Bowen ratio technique reduces offset effects. Recalibration
after two years of use is usually recommended to keep the RH probes
within their "as new" absolute accuracy specification; this is the goal
of the EBBR recalibration program conducted every two years.

The absolute value of the home signals varies with the voltage of the
battery that powers the EBBR data acquisition system. When the battery
condition is good, the home_15 value is typically between 40 and 55; the
home_30 value is typically between 15 and 30. When battery condition is
low, the home signals can be slightly lower, but then the data from some
individual sensors are questionable. Instances have occurred where low
battery condition allowed some sensors to function while others did not.
DQRs are written to identify such problems.

Unfortunately, the AEM does not always switch and occasionally hangs up.
Four cases are common:

1.  AEM fuse blown. When the fuse blows, the housing positions on the
    AEM are uncertain and usually yield home_15 and/or home_30 values of
    zero, although E15 at Ringwood, Oklahoma, showed -2.0 in this
    condition in May 1994. Usually the fuse blows because of too much
    friction on the exchange mechanism resulting from freezing rain or
    snow, built up dirt, or an electrical or electronic failure.

2.  AEM stuck at one position. Usually the right housing will stick in
    the down position (sometimes referred to in site operations log
    messages as the home position). When this happens, the home_15 and
    home_30 signal outputs are usually both equal to the proper home_30
    value, if the AEM fuse has not blown. There are exceptions to this
    of course, which included a period at the Central Facility EBBR in
    late 1992 when both home signals were 35.

3.  AEM stuck between the 15- and 30-minute positions. This situation
    usually produces a very small negative home value for both home_15
    and home_30, such as -0.2.

4.  AEM removed for service. Occasionally, an AEM has been removed from
    service for repair when no replacements were available (e.g., when
    the EBBR at E9, Ashton, Kansas, was removed on April 5, 1994). A
    resistor in the AEM circuitry had burned out, leaving the left
    housing in the bottom position (a rarity). This had resulted in both
    home signals showing somewhere from 67 to 73. After the AEM was
    removed, the aspirated housings were tied to the EBBR frame,
    approximately a meter apart. Without the AEM circuitry being
    present, the home signals floated to the thousands. On April 19, a
    refurbished AEM was installed and the home signals returned to
    normal.

The list above illustrates only some of the possibilities. Generally,
whatever their absolute values, if the home_15 and home_30 values are
practically the same in the 30-minute data, at least one of them is
incorrect, indicating that the sensible and latent heat flux estimates
are suspect. Unless both the home_15 and home_30 values are within
proper ranges, the sensible and latent heat values must be considered
incorrect. No other interpretation is appropriate. Even if we know the
AEM position situation and could thus recalculate fluxes from the
available data, those fluxes would still be corrupted with calibration
offsets, which are normally removed via the AEM switching process.

Most users of the EBBR data only receive the 30-minute data and not the
5- or 15-minute data. The QC flags in the 15-minute data might be useful
for a comprehensive evaluation of each EBBR sensor. For example, the
qcmin# check for battery condition in the 15-minute data is set to the
lowest value at which the sensors will typically operate reliably. Also,
soil moisture resistance ratios (rr_sm#, used before April 1996) or soil
moisture resistance (r_sm#, used beginning in April 1996) could be
examined to help determine when individual soil moisture values are
reliable. However, we do not expect every user of the EBBR to obtain the
15-minute data for such analyses. Finally, users of the data are
cautioned that the reliability and accuracy of some individual sensors,
such as soil moisture sensors, may be not optimal. The EBBR system was
not designed to observe all quantities extremely well because its
primary purpose is to provide sensible and latent heat flux estimates,
which are not particularly sensitive to the uncertainties of some of the
variables. For example, if accurate, reliable estimates of barometric
pressure and air temperature are needed, the values supplied by SMOS or
from external datasets, such as those from the Oklahoma Mesonet, should
be used. For soil moisture and temperature, we consider the EBBR
observations to be mostly inadequate for use in landsurface process and
hydrological models or submodels. On the other hand, we expect high
quality data on net radiation from EBBR stations because it is crucial
in the energy balance calculations. We expect soil heat flux values to
be good because they enter directly into the surface energy balance
calculations (but are typically small in magnitude compared to net
radiation). Unforeseen types of failures sometimes occur, e.g., the
ventilator for one of the temperature and humidity sensors stops. Such
problems are usually described in DQRs that are available for data
users.

When the Bowen ratio is between -1.6 and -0.45, "spikes" can occur in
the latent and sensible heat flux values.

**What are likely difficulties in comparing surface heat fluxes measured
by EBBR stations to results of numerical modeling efforts?**

One of the greatest difficulties in comparing model versus field data on
surface heat fluxes is caused by model calculations requiring soil
moisture information. The soil moisture across the SGP site can be quite
variable for summertime conditions. EBBR soil moisture data provide
measurements of average moisture content only in the top 5 cm. During
1996 and 1997, an effort led by Jeanne Schneider, University of Oklahoma
and supported by the National Oceanic and Atmospheric Administration for
GEWEX Continental-Scale International Project (GCIP), installed soil
water and temperature system (SWATS) profiling instrumentation at every
SGP extended facility, including every location with an EBBR station.
SWATS soil moisture and soil temperature data should be used for
modeling efforts, instead of the EBBR soil moisture and temperature
data.

Since summer 1995, at least three science team groups have tried
comparing model outputs with SGP site data: Jim Liljegren working with
Chris Doran at Pacific Northwest Laboratory; Marina Zivkovic working
with Jean-Francois Louis at Atmos. & Environmental Research, Inc., in
Cambridge, Massachusetts; and Sarah Fox working with Lee Harrison and
others at the State University of New York at Albany.

A cooperative program of sorts that has looked extensively at this type
of modeling is PILPS (Project for Intercomparison of Land-surface
Schemes). One conclusion of PILPS is that more observational data are
needed for developing large-scale models. For example, an article by
Betts et al. (1993) carries out a critical evaluation of European Center
for Medium Range Weather Forecasts (ECMWF) model outputs by using FIFE
data.

Some other potentially informative articles are as follows:

Avissar R, and MM Verstraete. 1990. "The representation of continental
surface processes in atmospheric models." *Reviews of Geophysics*
28:35-42.

Dickinson, RE, RM Errico, F Giorgi, and GT Bates. 1989. "A regional
climate model for the Western United States." *Climatic Change*
15:383-422.

Shuttleworth, WJ. 1991. "1. Insight from large-scale observational
studies of land/atmosphere interactions." *Surveys in Geophysics*
123-30.

# Data Quality

## Data Quality Health and Status

The status of the measurements made by the EBBR system can be found by
going to the ARM DQ HandS website at
[http://dq.arm.gov](http://dq.arm.gov/).

## Data Reviews by Instrument Mentor

Monthly reviews of the EBBR data are prepared by the mentor and
submitted to the Instrument Mentor Monthly Summary (IMMS) report
database. These reports are available at "Related Documents" on the EBBR
web page.

Beginning in FY2006, Data Quality Reports are not written for missing
data or for situations when QC flags clearly show that the data are
incorrect (this is true for most of the conditions listed below). DQRs
are written for periods when data are incorrect, when the situation is
not represented by QC flags in the data, and it's not obvious that the
data should have been flagged as incorrect.

## Data Assessments by Site Scientist/Data Quality Office

The following guidance has been provided by the EBBR mentor for use by
the Data Quality Office (DQO) in preparing their weekly assessment
report for the EBBR systems.

**EBBR Data Quality Guidance**

**David R. Cook**

**16 December 2006**

**Introduction:** The best way to tell someone what to look for in
assessing the EBBR data is to describe conditions that reflect correct
and incorrect data. For the most part, the QC checks provide adequate
guidance. However, there are conditions for which the QC flags do not
provide the needed guidance to be able to interpret the correctness of
the data. Therefore, please use the information below as further
guidance.

**Primary Measurements:** e (latent heat flux), h (sensible heat flux),
q (net radiation), ave_shf (average surface soil heat flux); le and h
are calculated, whereas q and ave_shf are measured. The QC limits set in
the ingest are appropriate for the measurements (primary and otherwise),
although there are times when legitimate values fall outside the QC
limits.

**Nuisance QC Flags:** The Bowen QC flag is frequently tripped,
particularly at sunrise or sunset, when the gradient of temperature can
be near zero. This condition produces spikes in h and e, which would be
quite obvious without the Bowen QC flag. Tripping of the Bowen QC flag
near sunrise or sunset should not be reported in the DQO assessment
reports. The hum_top and hum_bot QC flags will trip when the RH reported
by the T/RH sensor exceeds a certain value. However, the absolute
accuracy of the RH measurements is not important; the difference between
them is used to determine e. Therefore, the hum_top and hum_bot QC flag
condition should not be reported in the DQO assessment reports.

**Comparison of Data at Different EBBR Sites:** Generally, the
measurements can be compared favorably with those at adjacent sites,
keeping in mind that climate conditions from one side of the SGP ACRF to
another can differ sharply. There are some soil and surface vegetation
differences between sites as well, so comparisons may show significant
differences.

**Comparison of Data with the ECOR:** The only collocated ECOR and EBBR
are at E14/E13 (SGP Central Facility). Caution must be used in the
comparison of the two systems because they usually see different
vegetation surfaces. The best comparison can be made for straight north
or northwest wind directions, when both systems view the same grass
surface. For other directions, the two systems are viewing different
vegetation surfaces and the fluxes from the two will probably not be
similar, unless perhaps, the ground is snow covered. Except for the
E14/E13 and E21 sites, sensible and latent heat flux, and wind speed and
direction measurements can be compared for adjacent ECOR and EBBR
systems (which all view grassland), again remembering that there are
likely to be climatologically driven differences. No other measurements
can be reliably compared, mostly because the ECOR LI-7500 and sonic
anemometer are not meant to produce accurate measurements of anything
else that both systems measure.

**Comparison of Data with the SMOS:** SMOS systems are collocated with
EBBR systems at 8 of the 14 EBBR sites (exceptions are E2, E12, E18,
E19, E22, and E26). The measurements of upper EBBR temperature, RH, and
vapor pressure can be directly compared with the SMOS temperature, RH,
and vapor pressure. Even so, the EBBR RH may often be greater than that
from the SMOS, as it is allowed to drift upwards with time for longer
than is allowed for the SMOS. Wind speed and direction for the two
systems are at different heights (SMOS 10 m, EBBR \~3 m), so it is
normally expected that the SMOS wind speed will be greater than the EBBR
wind speed. Wind direction may be very similar, but may be somewhat
different if a frontal passage or strong advection is taking place. The
EBBR pressure measurement is not as accurate as that made by the SMOS,
but their trends and general level may be compared in a gross way.

**Comparison of EBBR Net Radiation with Solar and Infrared Station
(SIRS) Net Radiation:** EBBR net radiation measurements do not agree
with SIRS net radiation calculations when the effective sky temperature
is less than about -20°C and the EBBR net radiometer sensitivity
decreases rapidly with the further decrease in effective sky
temperature. First, the REBS longwave calibration is not performed to
very low temperatures, and second, the design of the net radiometer may
not allow for accurate low effective sky temperature measurements
anyway. Infrared thermometer (IRT), atmospheric emitted radiance
interferometer (AERI), and SIRS net radiation measurements are more
accurate under the condition of low effective sky temperatures.

The result of this situation is that the EBBR overestimates or
underestimates (it sounds odd, but it can be either) the nighttime
sensible heat flux (direction is to the surface) and overestimates
(sometimes by possibly a factor of 3) the nighttime latent heat flux.
This is not a major concern since the nighttime fluxes are usually quite
small anyway. Daytime fluxes are also affected, but since shortwave
radiation dominates the radiant energy budget, the sensible and latent
heat fluxes are both overestimated by only about 5 percent during a
sunny day and by about 2 percent on a cloudy day during summertime.
These errors are well within the 10 percent system error of the EBBR.

**Common Conditions Reflecting Correct or Incorrect Data:**

The EBBR data are only useful for particular wind directions at each
extended facility. Please use the following resources to help in
interpreting the EBBR data:

1\. QC flags in the EBBR data.

2\. Instrument Mentor Monthly Summaries (IMMS) at
http://www.db.arm.gov/IMMS/

3\. SGP EF Surface Conditions Observations (EFSCO) at
http://198.124.96.210:591/sfc_cond1/default.htm

4\. The information below on wind direction dependencies and conditions
that commonly cause incorrect data.

Wind Direction Dependencies (numbers are wind direction in degrees);
note that there are wind directions at most sites for which the fetch is
insufficient and therefore EBBR data are invalid. Appropriate fetch was
determined from a 1/40 measurement height to fetch ratio, resulting in a
required minimum fetch of 120 m. Particular attention should be paid to
the limited valid wind directions for the Central Facility EBBR. The
surface vegetation type for the EBBRs is grazed or ungrazed grassland
(refer to the EFSCO for state):

EF2: 71-137, 223-289

EF4: 0-158, 202-360

EF7: 0-244, 296-360

EF8: 0-224, 314-360

EF9: 0-360

EF12: 0-360

EF13: 0-52, 142-194, 328-360

EF15: 133-360

EF18: 138-325

EF19: 0-133, 151-360

EF20: 0-230, 310-360

EF22: 0-49, 139-360

EF25: 30-300

EF26: 0-33, 243-360

EF27: 20-156

Some conditions that commonly cause the EBBR primary measurements to be
incorrect or missing data are as follows:

-   Sensible and latent heat fluxes are not accurate during times when
    the Automatic Exchange Mechanism (AEM) is not functioning properly.
    The AEM switches the gradient measuring instrumentation between the
    top and bottom positions every 15 minutes; this reduces the effects
    of instrument offsets. Sometimes the AEM does not reach its full
    extent of travel, resulting in the home signal being zero.

-   Sensible and latent heat fluxes are sometimes incorrect when surface
    soil heat flow is out of range, as seen in the average soil heat
    flux (ave_shf).

-   Very light winds may be seen at nights for brief periods. Wind
    direction flops around a lot during low wind conditions (\< 1.5 m/s)
    and is often unreliable during those periods.

-   Missing data periods occur at times; this is usually a site data
    system collection/communication problem; it can also occur during
    replacement of the system with a newly calibrated unit. Missing data
    are sometimes filled in later from manual or automatic re-collection
    of the data.

## VAPs and Quality Measurement Experiments (QMEs)

The BA EBBR VAP represents a recalculation of sensible and latent heat
fluxes using wind speed and temperature gradient information in
conjunction with a bulk aerodynamic estimation technique. This VAP has
been implemented and 30-minute average files are available in the Data
Archive from 1995. Vegetation height and wind speed are used to
determine aerodynamic quantities that allow the calculation of sensible
and latent heat flux independent from measurements of net radiation and
soil surface heat flux. These calculations help to produce more
reasonable flux estimates when the Bowen ratio is between -1.6 and -0.45
(the Bowen ratio technique often produces unreasonable flux values under
this condition). Data source names take the form "sgp30baebbrE13.c1."
Presently, the files can be found in the Data Archive by looking under
c1 data sources. Results from the BA EBBR VAP can be seen in the second
plot in Section 5.2, Annotated Examples.

A second VAP involves the recalculation of sensible and latent heat
fluxes using Solar and Infrared Station (SIRS) net radiation
information; however, this VAP has not been implemented. This approach
may help to improve flux estimates during times when the EBBR net
radiation data are corrupted by dew, frost, or condensation inside or
outside of the net radiometer domes.

EBBR-related QMEs could include:

-   Comparison of EBBR-measured net radiation and SIRS-calculated net
    radiation. Comparison plots of EBBR net radiation and
    SIRS-calculated net radiation are produced by the DQO and displayed
    on the DQ HandS website. These comparison plots reveal significant
    differences between these two systems at times. A QME has not been
    performed as of yet.

-   Comparison of sensible and latent heat fluxes from EBBR and eddy
    correlation (ECOR) systems (only for comparisons between the EBBR
    and ECOR systems at the SGP Central Facility, and then only for very
    limited wind directions); no ECOR systems are collocated with EBBR
    systems over the same vegetation surface.

# Instrument Details

## Detailed Description

### List of Components

-   Vaisala T/RH probes at two heights (1 m separation), in aspirators

-   PRTD temperature probes at two heights (1 m separation), in
    aspirators

-   REBS Q\*7.1 Net Radiometer (at 2 m typical)

-   REBS SMP-2 (5 sets) Soil Moisture Probes at 2.5 cm depth

-   REBS HFT-3 (5 sets) Soil Heat Flow Plates at 5 cm depth

-   REBS STP-1 (5 sets) Soil Temperature Probes, integrated 0 to 5 cm

-   Met One Instruments 090C or 090D Barometric Pressure sensor (in
    enclosure)

-   Met One 020C Wind Direction sensor at 2.5 m

-   Met One 010C Wind Speed sensor at 2.5 m

-   PRTD Reference temperature of control box

-   REBS AEM

-   Pipe network structure for mounting of the instrumentation

-   Solar panel, battery, AC charger power source

-   Enclosure holding Campbell CR10, multiplexers, J-panels,
    communication equipment.

### System Configuration and Measurement Methods

The EBBR sensors (except for soil probes) are mounted on a triangular
pipe framework that sits on the soil surface. The net radiometer mount
extends from the south end of the EBBR frame.

A unique aspect of the system is the AEM, which helps to reduce errors
from instrument-offset drift. The AEM extends from the north end of the
frame. Aspirated radiation shields (which house the air temperature and
temperature/RH probes) are attached to the AEM. The openings of the
aspirated radiation shields face north to reduce radiation error from
direct sunlight.

The soil probes are buried just outside the view of and in an arc to the
south of the net radiometer.

The heights of the AEM aspirators are different at different extended
facilities and are dependent on maximum vegetation height; the vertical
separation between the two aspirators is 1 m at all extended facilities.
The heights or depths of all other sensors are the same at all
facilities.

The reference temperature sensor, barometric pressure sensor, data
logger equipment, and communication equipment are located in a control
box (weatherproof enclosure), which is attached at the northeast corner
of the EBBR frame.

The local area of influence upon Bowen ratio measurements is contained
within a horizontal distance of approximately 20 times the height of the
top aspirated radiation shield on the AEM. This distance varies among
the different extended facilities and for different times of the year
because of differences in maximum vegetation height, and therefore the
height at which the AEM is installed.

The manufacturer's (REBS) name for these systems is SEBS (Surface Energy
Balance System); this name appears in their systems documentation.

### Specifications

The accuracies cited below are generally those stated by the
manufacturer. They are sensor absolute accuracies and do not include the
effects of system (i.e., data logger) accuracies. Although it is not
known how some of the manufacturers have determined sensor accuracy, it
is properly the root square sum of any nonlinearity, hysteresis, and
non-repeatability, usually referenced as percentage of full scale.

The detection limit is normally restricted to the range (sometimes
called Calibrated Operating Range) over which the accuracy applies. In
the case of the EBBR, some of the detection limits are those determined
by the vendor (REBS) who performed the calibration, not by the
manufacturer of the sensor. Some manufacturers also specify an Operating
Temperature Range in which the sensor will function both

physically and electronically, even though the calibration may not be
appropriate for use throughout that range. When the manufacturer or the
calibrating vendor has listed no detection limits, none is stated below.

**Air temperatures:** Chromel-constantan thermocouple, Omega Engineering
Inc., REBS Model \# ATP-1, Detection Limits -30 to 40°C, Accuracy +/-
0.5°C.

**Temperature/RH Probe:** Operating Temperature Range -20 to 60°C.
Temperature: Platinum Resistance Temperature Detector (PRTD); Detection
Limits -30 to 40°C, Accuracy +/- 0.2°C RH: Capacitive element, Vaisala
Inc., Model #s HMP 35A and HMP 35D; Detection Limits 0% to 100% RH,
Accuracy +/- 2% (0-90% RH), +/- 3% (90-100%), uncertainty of RH
calibration +/- 1.2%.

**Soil Temperature:** Platinum Resistance Temperature Detector, MINCO
Products, Inc., REBS Model \# STP-1, MINCO Model \# XS11PA40T260X36(D),
Detection Limits -30 to 40°C, Accuracy +/- 0.5°C.

**Soil Moisture:** Soil Moisture Probe (fiberglass and stainless steel
screen mesh sandwich), Soiltest, Inc., REBS Model \# SMP-2, Soiltest
Model \# MC-300, Accuracy not specified by manufacturer (varies
significantly depending on soil moisture and soil type). Detection
limits for this sensor are limited by the ability to fit a polynomial to
the calibration data; for the SGP site, the detection limits are
approximately 1% to 50% by volume.

**Soil Heat Flow:** Soil Heat Flow Probes, Radiation & Energy Balance
Systems, Inc., Model #s HFT-3, HFT3.1, Accuracy not specified by
manufacturer.

**Barometric Pressure:** Barometric Pressure Sensor, Met One
Instruments, Model #s 090C-24/30-1, Detection Limits 24 to 30 kPa;
090C-26/32-1, Detection Limits 26 to 32 kPa; 090D-26/32-1, Detection
Limits 26 to 32 kPa; Accuracy for all +/- 0.14 kPa.

**Net Radiation:** Net Radiometer, Radiation & Energy Balance Systems,
Inc., Model Q\*6.1 or Q\*7.1, Accuracy +/- 5% of full-scale reading.

**Wind Direction:** Wind Direction Sensor, Met One Instruments, Model #s
5470, 020C, Detection Limits 0 to 360° physical (for greater than 0.3
ms-1 wind speed), 0 to 356° electrical, Accuracy +/- 3°.

**Wind Speed:** Wind Speed Sensor, Met One Instruments, model #s 010B
and 010C, Operating Temperature Range -50 to 85°C, Detection Limits 0.27
to 50 ms-1, Accuracy +/- 1% of reading. Operational Limit on speed 60
ms-1.

**Datalogger:** Campbell Scientific, Inc., Model CR10, Detection Limits
vary by voltage range selected, Accuracy +/- 0.1% of full scale reading.

## Theory of Operation

The EBBR stations use a standard Bowen ratio approach that has been
described by textbooks and articles. A general description can be found
in Brutsaert (1982). For an article, see p. 18,549 of the special FIFE
issue of the Journal of Geophysical Research (Vol. 97,
pp. 18,343‑19,110).

The surface energy balance equation is used:

q + ave-shf + h + e = 0,

where q is net radiation, ave_shf is the ground surface heat flow, h is
sensible heat flux, and e is latent heat flux. The units for the terms
in the equation above are watts per meter squared.

ave_shf is measured with five sets of soil heat flow, soil temperature,
and soil moisture probes. Soil heat flow at 5 cm (shf1, shf2, shf3,
shf4, shf5) measured with soil heat flow plates) and soil energy storage
(ces1, ces2, ces3, ces4, ces5) in the 0-5 cm layer (measured as the
change in temperature with time) are added to obtain surface soil heat
flow, as follows:

g1 = shf1 + ces1,

etc.,

where shf1 and ces1 are, respectively, the soil heat flow from the soil
heat flow plate and the change in energy storage measured from the soil
temperature probe of soil set #1. The expressions for g2, g3, g4, and g5
are similar. Soil moisture is used to adjust the measurements for soil
thermal conductivity, which affects the calibrations of the sensors.

Surface soil heat flow is then

ave_shf = (g1 + g2 + g3 + g4 + g5)/5,

When data from one or more soil set(s) is incorrect, that soil set(s)
can be eliminated and the average soil heat flow determined from the
remaining sets.

The Bowen ratio is measured as the ratio of the gradients of temperature
and vapor pressure (the latter calculated from RH and temperature)
across two fixed heights within three meters of the surface.

The Bowen ratio (B = h/e) is computed on the basis of the gradients and
the following computations are performed:

e = -(q + ave_shf)/(1 + B)

h = B \* e

More detailed information on these and other equations can be obtained
elsewhere, including from David Cook at Argonne National Laboratory. A
large manual provided by the manufacturer, REBS, Inc., describes the
general theory, gives rather complete information on each type of
sensor, and explains procedures for installation, operation, and
maintenance.

## Calibration

### Theory

Standard calibration procedures are employed by the vendor(s) of the
sensors and equipment used in the EBBR system when each EBBR unit is
returned for recalibration, approximately every two years.

### Procedures

Net Radiometer: Calibration is performed in a temperature-controlled
black-body cavity chamber against a transfer standard. The light source
is a tungsten-halide lamp. The transfer standard was calibrated both in
the temperature-controlled cavity chamber and by comparison to an Eppley
precision pyranometer outdoors. Wind speed effects are also taken into
consideration by ventilating the radiometers in the calibration chamber
and outdoors. The transfer standard is traceable to NIST through the
Eppley pyranometer using a shading technique. Shortwave and longwave
calibrations are different and so they are applied appropriately for
daytime and nighttime conditions in the EBBR programming. The longwave
calibration performed by REBS does not provide correct measurements
under conditions of low effective sky temperatures (below about -30°C).

### History

The EBBR systems are returned to REBS approximately every two years for
calibration of all sensors and data logger equipment. Some of the
calibrations are performed by REBS themselves while some are performed
by manufacturers of the equipment. For various reasons (the need to
provide and calibrate spare sensors, frequent AEM failures, etc.) the
time between recalibrations of EBBR units has sometimes been greater
than two years; REBS is a small company and has little flexibility to
reprioritize rapidly for individual customers.

## Operation and Maintenance

### User Manual

A user manual is available from REBS for the SEBS systems. One copy is
kept at the SGP Central Facility and the mentor keeps one copy.

### Routine and Corrective Maintenance Documentation

SGP Site Operations (Site Ops) personnel maintain preventative
maintenance, corrective maintenance, and engineering logs. Maintenance
and system checks are performed in accordance with a set of procedures
written by Site Ops and the mentor. These procedures are maintained in
print form at the SGP Central Facility and in digital form on Site Ops
laptops taken into the field during preventative maintenance visits to
the EBBR systems.

### Software Documentation

EBBR programs are maintained on SGP Site Ops computers at the SGP
Central Facility, on laptops used by Site Ops during preventative
maintenance visits, and at REBS. The mentor maintains print copies and
some digital copies.

### Additional Documentation

Six-month EBBR checks are maintained on the SGP [Operations Management
Information System (OMIS) website](http://www.ops.sgp.arm.gov/).

## Glossary

Bowen Ratio − the ratio of the sensible heat flux to the latent heat
flux.

Sensible Heat Flux − the transfer of sensible heat (enthalpy) between
the surface and the air, or vice versa.

Latent Heat Flux − the transfer of latent heat (heat released or
absorbed by water) between the surface and the air, or vice versa.

Net Radiation − the net difference in downwelling and upwelling solar
plus terrestrial radiation.

Soil Heat Flow − the transfer of sensible heat (enthalpy) in the soil,
towards the surface or away from the surface.

## Acronyms

AEM Automatic Exchange Mechanism

AERI atmospheric emitted radiance interferometer

ARM Atmospheric Radiation Measurement (Program)

BA Bulk Aerodynamic Technique

DQO Data Quality Office

DQR Data Quality Report

EBBR Energy Balance Bowen Ratio

ECMWF European Centre for Medium-Range Weather Forecasts

ECOR Eddy Correlation System

FIFE First ISLSCP Field Experiment

GCIP GEWEX Continental-Scale International Project

IMMS Instrument Mentor Monthly Summary

IRT infrared thermometer

MDS Meta Data System

NIST National Institute of Standards and Technology

OMIS Operations Management Information System

PILPS Project for Intercomparison of Land-surface Schemes

PRTD Platinum Resistance Temperature Detector

QC quality control

QME Quality Measurement Experiment

RH relative humidity

RMSE root-mean-square error

SEBS Surface Energy Balance System

SGP Southern Great Plains

SIRS Solar and Infrared Station (Broadband Radiometers)

SMOS Surface Meteorological Observation Station

SWATS soil water and temperature system

VAP value-added product

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

## Citable References

Avissar, R and MM Verstraete. 1990. "The representation of continental
surface processes in atmospheric models." *Reviews of Geophysics*
28:35-42.

Betts, AK, and JH Ball, ACM Beljaars. 1993. "Comparison between the land
surface response of the ECMWF model and the FIFE-1987 data." *Quarterly
Journal of the Royal Meteorological Society* 119:975-1001.

Brutsaert, WH. 1982. *Evaporation in the Atmosphere*. D. Reidel
Publishing Company, Dordrecht, Holland, pp. 210-212.

Dickinson, RE, RM Errico, F Giorgi, and GT Bates. 1989. "A regional
climate model for the Western United States." *Climatic Change*
15:383-422.

Fritschen, LJ and LW Gay. 1979. *Environmental Instrumentation*.
Springer-Verlag, New York, p. 216.

Fritschen LJ, P Qian, ET Kanemasu, D Nie, EA Smith, JB Steward, SB
Verma, and ML Wesely. 1992. "Comparisons of Surface Flux Measurement
Systems Used in FIFE 1989." *Journal of Geographical Research*
97(D17):18,697-18,713.

Shuttleworth, WJ. 1991. "1. Insight from large-scale observational
studies of land/atmosphere interactions." *Surveys in Geophysics*
12:3-30.

Wesely, MW, DR Cook, and RL Coulter. 1995. "Surface Heat Flux Data from
Energy Balance Bowen Ratio Systems." Preprints of the *Ninth Symposium
on Meteorological Observations and Instrumentation*, pp. 486-489.
Charlotte, North Carolina, March 27-31 1995, American Meteorogical
Society, Boston, Massachusetts.

## Bibliography

Field, RT, L Fritschen, ET Kanemasu, EA Smith, J Stewart, S Verma, and W
Kustas. 1992. "Calibration, comparison, and correction of net radiation
instruments used during FIFE." *Journal of Geophysical Research*
97:16681-18695.

Fritschen, L, and JR Simpson. 1989. "Surface energy and radiation
balance systems: General description and improvements." *Journal of
Applied Meteorology* 28:680-689.

Halldin, S, and A Lindroth. 1992. "Errors in net radiometry: Comparison
and evaluation of six radiometer designs." *Journal of Atmospheric
Oceanic Technology* 9:762-783.

Heilman, JL, and CL Brittin. 1989. "Fetch requirements for Bowsen ratio
measurements of latent and sensible heat fluxes." *Agricultural and
Forest Meteorology* 44:261-273.

Lewis, JM. 1995. "The story behind the Bowen ratio." *Bulletin of the
American Meteorological Society* 76:2433-2443.