CEOP/EOP-1 GAPP Ft. Peck Hourly Surface Meteorology, Flux, and Radiation Data Set
1.0 Contact Information
1.1 UCAR/JOSS Contact
Steven F Williams
Data Specialist
UCAR/JOSS
P.O. BOX 3000
Boulder, CO, USA, 80307-3000
Telephone: 303-497-8987
Facsimile: 303-497-8158
E-Mail Address: sfw@ucar.edu
1.2 GAPP Contact
Tilden Meyers
NOAA/ATDD
P.O. Box 2456
Oak Ridge, TN 37831-2456
USA
Telephone: 423-576-1233
E-mail: meyers@atdd.noaa.gov
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) Ft. Peck 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
http://www.joss.ucar.edu/ghp/ceopdm/ under the link "CEOP EOP-1 Reference
Site Data Sets"
3.1 GAPP Ft. Peck 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
7 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})
---------------
n
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
at http://www.joss.ucar.edu/ghp/ceopdm/.
3.2 Station Information
The following is a complete description of the station information
provided with this CEOP GAPP Ft. Peck data set. Table 1 details the
station list parameters. GAPP Ft. Peck 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. [Ft. Peck]
Identification Type Internal ID number type. [32]
Latitude Station Latitude. [48.31000]
Longitude Station Longitude. [-105.10000]
Occurrence Station occurrence. [0]
Lat/Lon Accuracy Number of digits accuracy
in lat/lon values. [2]
Name Expanded station name. [GAPP:Ft. Peck]
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. [30]
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. [634]
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 Ft. Peck 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
http://www.joss.ucar.edu/ghp/ceopdm/ 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
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 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,
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.