*Champaign, Illinois.*

During the summer of 1996, a second flux/meteorological system was
installed just south of Champaign, Illinois on a farm owned and operated
by John Reifsteck (Word Wide Web site is
http://W3.ag.uiuc.edu/INFOAG/cyberfarm/reifstck/index/html). This farm
(40º 00.366\' N, 88º 17.512\' W) is within the GEWEX/GCIP large scale
area north central (NC), and just on the northeastern edge of the LSA
southeast (SE) region. The site characteristics are typical of those
found throughout the midwestern U.S., with most of the land in
agricultural production. The soil (silt loam) has a bulk density of 1.5
g/cm^3^ with sand, silt, and clay fractions of 5%, 70%, and 25%,
respectively. The farm has been in continuous no-till since 1986,
alternating each year between corn and soybeans. In 1996, the field
consisted of soybeans, corn in 1997 and again soybeans in 1998. Corn was
planted in 1999 and soybeans will be grown in the year 2000. From
measured leaf area index data and measures of visible reflectance, files
containing leaf area index information for each day in the growing
season have been generated for 1997, 1998 and 1999. The file names are
BV97_LAI.prn, BV98_LAI.prn, BV99_LAI.prn

Additional information

[Year]{.underline} [crop]{.underline} [Planting Date]{.underline}
[Harvest Date]{.underline}

1996 Soybeans \-- 10/25

1997 corn 04/18 10/19

1998 Soybeans 06/01 10/10

1999 Corn 05/10 10/23

The site is within 5 km of the NOAA\'s SURFRAD site, which provides
measurements of direct and diffuse shortwave radiation and the incoming
and outgoing longwave components. The flux/meteorological system is
nearly identical to the Little Washita System with the exception that
the instrumentation and solar panels are mounted on a scaffolding tower.

Site: Champaign, Illinois (near Bondville)

site latitude 40 deg 00.366 min N

longitude 88 deg 22.373 min W

elevation approx 300 m

**2. Methodology**

Traditionally, the use of the eddy correlation method (Businger, 1987;
Baldocchi et al., 1988) has been constrained to mainly short term
intensive field campaigns. Improvements in instrument design, stability,
and power requirements over the past decade now allow for nearly
continuous measurements of sensible and latent energy fluxes using the
eddy covariance technique. Using this technique, the average vertical
turbulent eddy fluxes of sensible and latent heat (and other scalars)
are determined as

where $w$ is the vertical velocity component of the wind vector, and
$\chi$ is the scalar of interest (e.g. water vapor concentration). Here,
the bracketed quantities denote an average or "mean" that is subtracted
from the instantaneous values to obtain the fluctuating component.
Average vertical turbulent fluxes ($\overline{w^{'}\chi^{'}}$ ) are
computed in real time using a digital recursive filter (200 s time
constant) for the determination of a running "mean" from which the
instantaneous values are subtracted. An averaging period of 30 minutes
(denoted by the overbar) is used and is considered large enough for
statistical confidence in the covariance quantity but is short enough to
resolve the structure of the diurnal cycle.

Wind vector measurements made at experimental sites that are not
perfectly flat can result in non-zero vertical wind velocities measured
from the "vertical " coordinate system of the measurement platform. At
the end of an average period, vertical turbulent fluxes perpendicular to
the mean horizontal wind (which generally follows the contour of the
land surface) are obtained by mathematically rotating the coordinate
system of the measurement frame of reference (sonic anemometer) to
obtain a zero mean vertical and transverse velocity
($\overline{w}\text{ = }\overline{v}\text{ = 0}$). Details of this
procedure described by Wesely (1969) are outlined by Businger (1986) and
Baldocchi et al., (1988).

The three components of the wind vector are determined with a sonic
anemometer ( R2, Gill Instruments, Hampshire, England). The stable
long-term operational characteristics of this instrument and its ability
to continue measurements during cold weather and light rain events
(Yellard et al., 1994), as well as its low power consumption, were
important considerations in the selection of this anemometer. The
symmetric head design of the R2 with its slender support structure
produces little flow distortion (Grelle and Lindroth, 1994) and is well
suited for measurements in the the relatively flat and open locations of
the Little Washita Watershed and Champaign, Illinois sites Fast response
water vapor and CO~2~ concentration measurement are made with an
open-path, fast response infrared gas analyzer (Auble and Meyers, 1992).
This sensor was used extensively for flux measurements during recent ARM
(Doran et al., 1992) and BOREAS (Baldocchi et al., 1997) experiments. In
a recent evaluation of open and closed path sensors for water vapor and
CO~2~ concentrations, Leuning and Judd (1996) found that for the
measurement of CO~2~, this sensor displayed minimal cross sensitivity to
water vapor (see Leuning and Moncrieff, 1990).

Standard meteorological data collected at each site. The following are
the variables, in order as they appear in the file.

jday Julian Day

time LST, half hour ending

w_speed propeller anemometer (10 meters, Bondville ISIS)

w_dir wind direction (10 meters, Bondville ISIS)

Ta air temperature (C), at 3 m

RH relative humidity at 3 m

Pres surface pressure in mb

Rg incoming global radiation (W/m2)

Par_in incoming visible radiation (0.4‑0.7 um) in uE/m2/s

Par_out outgoing or reflected visible light

Rnet net radiation (W/m2)

GHF soil or ground heat flux (W/m2)

rain total rain for half hour (inches)

wet wetness sensor (in voltage with higher values indicating wetness)

IRT surface or skin temp (C)

2_cm soil temp at 2 cm (C)

4_cm soil tmep at 4 cm

8_cm soil temp at 8 cm

16_cm soil temp at 16 cm

32_cm soil temp at 32 cm

64_cm soil temp at 64 cm

u_bar average wind vector speed (m/s)

u\'w\' kinematic shear stress (m2/s2)

u\'2 streamwise velocity variance (m2/s2)

v\'2 crosswind velocity variance (m2/s2)

w\'2 vertical velocity variance (m2/s2)

H sensible heat flux (W/m2)

LE latent energy flux (W/m2)

CO2 CO2 flux (mg CO2/m2/s)

LW_in downwelling longwave from sky (W/m2)

sm_5 soil volumetric water content at 5 cm zone (after November 19 1997)

sm_20 soil volumetric water content at 20 cm zone (after November 19
1997)

sm_60 soil volumetric water content at 60 cm zone (after November 19
1997)

The eddy covariance sensors are located at 6 m AGL. The bulk density of

the soil is 1.4 gm/cm3. The site is currently in corn stubble (like it
would look

after combining). I am currently working up more soils data, and will
have that

information available shortly.

The standard meteorological sensors (Table 1) are sampled every 2 s with
a datalogger and multiplexor (CR21x, Campbell Scientific, Inc.) and
averages are computed every 30 minutes, coincident with the eddy
covariance data.

*Data Acquisition*

A laptop computer is configured in a mulitasking mode to simultaneously
perform three operations. For the first and foremost task, measurements
of the three componenets of the wind vector along with the speed of
sound (from which the virtual temperature can be derived) are digitally
sent from the sonic anemometer (which includes the digitized H~2~O and
CO~2~ signals from the IRGA) to the laptop computer, which is housed in
a small environmental enclosure. In the second task, the computer
retrieves the standard meteorological data from the CR21X datalogger
every 30 minutes and appends the data to an existing file. After
midnight, the covariance data and standard meteorological data are
copied to separate files with a name, year and calendar day header. The
computer is equipped with a modem and cellular phone in order to
retrieve the data and conduct occasional system checks. On average, data
are retrieved from the laptop computers about once every two days.

*Power Operation and Management*

To avoid the constraints of using standard line power, the entire
flux/meteorological system is designed to operate on 12 volts DC making
it truly remote and portable. The entire flux system, including all the
instruments and data logging devices are powered by nine deep-cycle 12
volts DC batteries that are charged daily with solar panels ( M75,
Siemans, Inc.). Each solar panel is capable of producing 3 amperes at 12
volts in full sunlight. The batteries are enclosed in an insulated
container that is 2/3 submerged into the ground near the base of the
tower. Ten solar panels are required at the Illinois site while eight
are used at the Little Washita location. Each charging system is
controlled with a 30 ampere regulator. The regulator is equipped with a
low voltage disconnect option that disconnects electronic devices with
the largest power consumption when the battery voltage falls below 11.5
VDC. Table (2) lists the major instruments and corresponding power
requirements. The entire system continuously draws about 3 amperes at 12
VDC. The 21X datalogger and cellular phone are connected directly to the
batteries and operate continuously since they have low power demands.
When the regulator disconnects the computer because of low voltage (i.e.
long periods of cloudy weather), only standard meteorological data are
logged. After the batteries are charged to 12.5 VDC, the computer, IRGA
and sonic are reconnected and logging of the flux data resumes. As will
be discussed later, this happens infrequently and only during the winter
months when cloudy conditions persist during the relatively short
daylight hours.

**REFERENCES**

Auble, D. L, T. P. Meyers, 1992. An open path, fast response infrared
absorption gas analyzer for H~2~O and CO~2~, *Boundary-Layer
Meteorology*, 59, 243-256.

Atlas, R., N. Wolfson and J. Terry, 1993. The effect of SST and soil
moisture anomalies on GLA model simulations of the 1988 U.S. summer
drought, *J. of Climate*, 2034-2048.

Baldocchi, D. D. and T. P. Meyers, 1991. Trace gas exchange at the floor
of a deciduous forest: I Evaporation and CO~2~ efflux, *Journal of
Geophysical Research, Atmospheres*, 96, 7271-7285.

Baldocchi, D. D., B. B. Hicks and T. P. Meyers, 1988: Measuring
biosphere‑atmosphere exchanges of biologically related gases with
micrometeorological methods. *Ecology* 69:1331‑1340.

Chen. T. H., A. Henderson-Sellers, and A. J. Pitman, 1994. Recent
progress in the Project for

Intercomparison of Land Surface Parameterization Schemes (PLIPS), *GEWEX
News*, 4, 8-9.

Dolske, D. A. and D. F. Gatz, 1985. A field intercomparison of methods
for the measurement of article and gas dry deposition, *J. Geophysical
Research*, 90, 2076-2084.

Doran, J. C., F. J. Barnes, R. L. Coulter, T. L. Crawford, D. D.
Baldocchi, L Ballick, D. R. Cook, D. Cooper, R. J. Dobosy, W. A. Dugas,
L. Fritschen, R. L. Hart, L Hipps, J. M. Hubbe, W. Gao, R. Hicks, R. R.
Kirkham, K. E. Kunkel, T. J. Martin, T. P. Meyers, W. Porch, J. D.
Shannon, W. J. Shaw, E. Swiatek, and C. D. Whiteman, 1992. The Boardman
Regional Flux Experiment, *Bulletin of the American Meteorological
Society*, 73, 1785-1795.

Garratt, J. R., 1993. Sensitivity of climate simulations to land-surface
and atmospheric boundary

layer treatments - a review, *J. of Climate*, 6, 419-449.

Grelle, A. and A. Lindroth, 1994. Flow distortion by a Solent Sonic
anemometer: wind tunnel calibration and its assessment for flux
measurements over forest and field, *Journal of Atmospheric and Oceanic
Technology*, 11, 1529-1542.

Henderson-Sellers, A., 1993. A factorial assessment of the sensitivity
of the BATS land-surface parameterization scheme, *J. of Climate*, 6,
227-247.

Henderson-Sellers, A. and R. E. Dickinson, 1992. Intercomparison of land
surface parameterization launched, *EOS*, 73, 195-196.

Jacquemin, B., J. Noilhan, 1990. Sensitivity study and validation of a
land surface parameterization using the HAPEX-MOBILHY data set,
*Boundary-Layer Meteorology*, 52, 93-134.

Leuning, R. and J. Moncrieff, 1990. Eddy covariance CO2 flux
measurements using openpath and closed-path CO2 analyzers-corrections
for analyzer water vapor sensitivity and damping of fluctuations in air
sampling tubes, *Boundary-Layer Meteorology*, 53, 63-76.

Leuning, R. and M. J. Judd, 1996. The relative merits of open- and
closed-path analyzers for the measurement of eddy fluxes, *Global Change
Biology*, 2, 241-253.

Meehl, G. A. and W, M. Washington, 1988. A comparison of soil-moisture
sensitivity in two global climate models, *J. Atmospheric Sciences*, 45,
1476-1492.

Meyers, T. P. and D. D. Baldocchi, 1993. Trace gas exchange at the floor
of a deciduous forest: II O~3~ and SO~2~ deposition rates, *Journal of
Geophysical Research, Atmospheres*,98,2519- 2528.

Meyers, T. P. and D. D. Baldocchi, 1988, A comparison of models for
deriving dry deposition fluxes of O~3~ and SO~2~ to a forest canopy.
*Tellus* 40B:270‑284.

Pan, H. L., and L. Mahrt, 1987. Interaction between soil hydrology and
boundary-layer development, *Boundary-Layer Meteorology*, 38, 185-202.

Sato, N., P. J. Sellers, D. A. Randall, E. K. Schneider,, J. Shukla, J.
L. Kinter III, Y. T. Hou, and E. Albertazzi, 1989. Effects of
implementing the simple biosphere model in a general circulation model,
*J. Atmospheric Science*, 46, 2757-2782.

Sellers, P. J., and J. L. Dorman, 1987. Testing the simple biosphere
(SiB) using point micrometeorological and biophysical data, *J. Climate
Applied Meteorology*, 26, 622-651.

Sellers, P. J., Y. Mintz, Y. C. Sud, and A. Dalcher, 1986. A simple
biosphere model (SiB) for use within general circulation models, *J.
Atmospheric Science*, 43, 505-531.

Troen, I., and L. Mahrt, 1986. A simple model of the atmospheric
boundary layer; sensitivity to surface evaporation, *Boundary-Layer
Meteorology*, 37, 129-148.

Vogel, C. A., D. D. Baldocchi, A. K. Luhar, K. S. Rao, 1994. A
comparison of a hierarchy of models for determining energy balance
components over vegetation canopies (submitted).

Yellard, M. J., P. K. Taylor, I. E. Consterdine, and M. H. Smith, 1994.
The use of the inertial dissipation technique for shipboard wind stress
determination, *J. Oceanic and Atmospheric Technology*, 11,1093-1108.

Zeller, K. F., 1993. Eddy diffusivities for sensible heat, ozone, and
momentum from eddy correlation and gradient measurements, USDA Forest
Service Research Paper RM-313.

Table 1. Meterological variables measured at NOAA Energy Flux Monitorin
Sites along with model number and manufacturer of instrumentation used.

  -----------------------------------------------------------------------
  **Meteorological        **Manufacturerer**      **model number**
  Variable**                                      
  ----------------------- ----------------------- -----------------------
  Air Temperature and RH  Vaisala                 50Y

  Net Radiation           Radiation and Energy    Q\*7
                          Balance Systems (REBS)  

  Global Radiation        LI-COR                  LI-200 SB

  Precipitation           Texas Instrument        

  Wetness                 ATDD                    \-

  Soil Heat Flux          REBS                    

  PAR                     LI-COR                  LI-190 SB

  Atmospheric Pressure    Vaisala                 PTB101B

  Surface Temperature     Everest                 4000A

  Soil Temperature        ATDD                    \-

  Soil Moisture           Vitel                   hydra
  -----------------------------------------------------------------------