CEOP/EOP-1 GAPP Bondville Hourly Surface Meteorology, Flux, and Radiation Data Set

1.0 Contact Information

1.1 UCAR/JOSS Contact

   Steven F Williams
   Data Specialist
   P.O. BOX 3000
   Boulder, CO, USA, 80307-3000

   Telephone: 303-497-8987
   Facsimile: 303-497-8158

   E-Mail Address:

1.2 GAPP Contact

   Tilden Meyers 
   P.O. Box 2456 
   Oak Ridge, TN 37831-2456

   Telephone: 423-576-1233
2.0 General Description
This data set contains the Coordinated Enhanced Observing Period (CEOP)
Enhanced Observing Period 1 (EOP-1) Global Energy and Water Cycle
Experiment (GEWEX) Americas Prediction Project (GAPP) Bondville Hourly
Surface Meteorology, Flux, and Radiation Data Set. This data set contains
hourly data from a single station for the CEOP EOP-1 time period (01 July
2001 to 30 September 2001). The University Corporation for Atmospheric
Research/Joint Office for Science Support (UCAR/JOSS) did not perform
quality control processing on this data set.

3.0  Detailed Data Description

This data set is also available on-line in 30-minute native format at under the link "CEOP EOP-1 Reference
Site Data Sets"

3.1 GAPP Bondville Algorithms

This hourly data set was formed by extracting the top of the hour
observations from the 30 minute native format data. The data were 
provided in local standard time and were converted to UTC time by  adding
6 hours to the local standard time. The U and V wind  components were
computed from wind speed and direction. The dew point was 
computed from the temperature and relative humidity (Bolton, 1980).
Specific Humidity values were computed from the calculated dew point
and station pressure using formulas from Wexler and Wildhack (1963).
The hourly precipitation was formed by summing the previous bottom
of the hour and current top of the hour 30 minute values.

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 powee 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

                           w'X' = $(w-{w})(X-{X})

where w is the vertical velocity component of the wind vector,  and X 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.  The $
represents the summation from i = 1 to n.  Average vertical turbulent 
fluxes (w'X') 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 (w=v=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 CO2 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 
CO2 concentrations, Leuning and Judd (1996) found that for the measurement
of CO2, this sensor displayed minimal cross sensitivity to water vapor 
(see Leuning and Moncrieff, 1990).     

More information regarding this site can be found under the  CEOP Reference
Site Station Characteristics link on the UCAR/JOSS CEOP Data Management page

3.2 Station Information

The following is a complete description of the station information
provided with this CEOP GAPP Bondville data set. Table 1 details the
station list parameters. GAPP Bondville values for each parameter are
listed in brackets at the end of each line. The beginning and ending dates
for the period of coverage are in Universal Time Coordinated (UTC). The
Identification Type field is network dependent and indicates the source of
the Identification field. The Occurrence field is an integer value used to
indicate co-located stations. Note that when a particular parameter is
unknown for a station, either a blank, a question mark, or all 9's will
appear in that parameter's position. For a complete list of Country,
State, and County values, refer to the document in the references (Section
5.0). Possible platform types and frequency values are listed in Tables 2
and 3, respectively. Note that only those platform types present in the
CEOP EOP-1 data have been listed. 

Table 1

Parameter                Description
---------                -----------
Identification           ID in data.        [Bondville]
Identification Type      Internal ID number type.  [32]
Latitude                 Station Latitude.  [40.00610]
Longitude                Station Longitude. [-88.29000]
Occurrence               Station occurrence. [0]
Lat/Lon Accuracy         Number of digits accuracy 
                         in lat/lon values.  [2]
Name                     Expanded station name. [GAPP:Bondville]
Commissioned Flag        `(C)' indicates commissioned station,
                         `(N)' indicates station which is NOT
                         commissioned. [(N)]
Begin Period of Coverage Beginning date of period of coverage
                         (YYYYMMDD). [20010701]
End Period of Coverage   End date of period of coverage
                         (YYYYMMDD). [20010930]
Country                  Country in which station is located. [US]
State                    State code.  [17]
County                   County code. [???]
UTC offset               Hour Offset from UTC time. [0.00]
DST switch               'y' indicates station does switch to
                         Daylight Savings Time (DST). 'n' indicates 
                         station does not switch to DST.   [n]
Platform type            Collection Platform. See Table 2. [264] 
Reporting Frequency      Frequency of data collection.  [30min]
Elevation                Station elevation. [213]
Fixed/Mobile flag        Flag indicating if station has fixed
                         location. 'f' indicates a fixed station.
                         'm' indicates a mobile station. [f]

Table 2

Platform Type  Description
-------------  -----------
264            CEOP Reference Site Platform

Table 3                                            
Reporting Frequency
30 minute

3.3  Detailed Format Description
The CEOP EOP-1 GAPP Bondville Hourly Surface Meteorology, Flux, and
Radiation Data Set contains 10 metadata parameters and 22 data
parameters.  The metadata parameters describe the station location and
time at  which the data were collected. The time of observation is
reported  both in Universal Time Coordinated (UTC) Nominal and UTC actual
time.   Days begin at UTC 0100 and end at UTC 0000 the following day. Note
that  missing parameter values are indicated by "-999.99".  The table
below  details the data parameters in each record. 

Parameters                   Units 
----------                   -----
Date of Observation          UTC Nominal 
Time of Observation          UTC Nominal 
Date of Observation          UTC Actual
Time of Observation          UTC Actual
CSE Identifier               Abbreviation of CSE name
Reference Site Identifier    Abbreviation of Site name
Station Identifier           Reference Site Dependent 
Latitude                     Decimal degrees, South is negative
Longitude                    Decimal degrees, West is negative
Station Elevation            Meters 
Station Pressure             Hectopascals (mb) 
Dry Bulb Temperature         Celsius 
Dew Point                    Celsius 
Relative Humidity            Percent
Specific Humidity            g/kg
Wind Speed                   m/s
Wind Direction               Degrees 
U Wind Component             m/s
V Wind Component             m/s
Total Precipitation          mm
Snow Depth                   cm     
Sensible Heat Flux           W/m2
Latent Heat Flux             W/m2
Incoming Shortwave Radiation W/m2
Outgoing Shortwave Radiation W/m2
Incoming Longwave Radiation  W/m2
Outgoing Longwave Radiation  W/m2
Net Radiation                W/m2
Skin Temperature             Celsius
CO2 Flux                     uMoles/m2/s
Incoming PAR                 uMoles/m2/s
Outgoing PAR                 uMoles/m2/s

3.4  Data Remarks

This data set contains only the hourly observations for the CEOP EOP-1
time period. This data set is also available on-line in native format at under the link "CEOP EOP-1 Reference
Site Data Sets".

4.0  Quality Control Processing

UCAR/JOSS performed limited gross limit and visual checks on this data
set. No data values have been changed.

5.0  References

Auble, D. L, T. P. Meyers, 1992. An open path, fast response infrared 
     absorption gas analyzer for H2O and CO2, 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 CO2 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. 

Bolton, D., 1980: The computation of equivalent potential temperature.,
     Mon. Wea. Rev., 108, pp 1046-1053.

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.

Department of Commerce - National Institute of Standards and Technology
     (NIST), 1985: Federal Information Processing Standards Publication
     10-3 Countries, Dependencies, & Areas of Special Sovereignty.
     Department of Commerce - NIST, Washington, DC.

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
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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,

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 O3 and SO2 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 O3 and SO2 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).

Wexler, A., and W. A. Wildhack, 1963:  Humidity and Moisture.
     Vol. 3: Fundamentals and Standards.  Reinhold Publ. Corp., 562 pp. 

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,

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.