BOREAS TF-10 NSA-YJP Tower Flux, Meteorological, and Porometry Data

Summary

The BOREAS TF-10 team collected tower flux and meteorological data at two sites, 
a fen and a young jack pine forest, near Thompson, Manitoba, Canada, as part of 
BOREAS.  A preliminary data set was assembled in August 1993 while field testing 
the instrument packages, and at both sites data were collected from 15-Aug to 
31-Aug.  The main experimental period was in 1994, when continuous data were 
collected from the young jack pine site from 23 May to 20 Sep.  Upon examination 
of the 1994 data set, it became clear that the behavior of the heat, water, and 
carbon dioxide fluxes throughout the whole growing season was an important 
scientific question, and that the 1994 data record was not sufficiently long to 
capture the character of the seasonal behavior of the fluxes.  Thus, the young 
jack pine site was operated from 08-May to 07-Nov in 1996 in order to collect 
data from spring melt to autumn freeze-up.  All variables are presented as 30-
minute averages.  Supporting data were also collected to describe the surfaces 
state and to provide the information, in association with the flux data, to 
build SVAT models. For the young jack pine site, these supporting data included 
stomatal conductance measurements.  The data are stored in tabular ASCII files.
This guide/data set deals exclusively with the YJP site. Check Section 1.6 for 
the TF-10 fen site data set.

Table of Contents

1 Data Set Overview
2 Investigator(s)
3 Theory of Measurements
4 Equipment
5 Data Acquisition Methods
6 Observations
7 Data Description
8 Data Organization
9 Data Manipulation
10 Errors
11 Notes
12 Application of the Data Set
13 Future Modifications and Plans
14 Software
15 Data Access
16 Output Products and Availability
17 References
18 Glossary of Terms
19 List of Acronyms
20 Document Information

1. Data Set Overview

1.1 Data Set Identification                                   

BOREAS TF-10 NSA-OJP Tower Flux, Meteorological, and Porometry Data

1.2 Data Set Introduction

The meteorological data collected from the fen and Young Jack Pine (YJP) towers 
represent, in some sense, polar opposites of the range of surface climate 
conditions expected in the boreal forest.  The fen is normally characterized by 
abundant water close to, or located at, the surface, whereas the YJP site can be 
one of the driest surfaces in the boreal forest.  Jack pine generally inhabit 
well-drained, sandy soils where, in the absence of regular precipitation, a 
significant water deficit can develop.  The data presented here bear out the 
contrast in the surface climate conditions experienced by the two sites.  For 
example, in the driest periods in the summer of 1994 it was common to measure 
mid-afternoon Bowen ratios in the range of 10 to 15, leading to the 
characterization of the site as a Green Desert; at the same time, the 
typical Bowen ratio at the fen seldom exceeded 1.0, and was usually closer to 
0.8.

The YJP site can be fairly described as a fast response surface in that there 
were major and rapid changes in flux behavior, especially in evaporation, as the 
site was wetted or when it dried down.  No such behavior could be ascribed to 
the fen because of the steadier supply of surface water.

1.3 Objective/Purpose

This project is concerned with the spatial heterogeneity of surface energy 
fluxes in the northern boreal forest.  The study was designed to compare surface 
radiation, energy, water, CO2 fluxes, and their biophysical controls at both 
wetland and upland forest sites within the northern boreal forest.  Specific 
objectives of the study were as follows:

i) To quantify the differences between surface-atmosphere interactions between 
the sites.

ii) To compare hydrological estimates of basin evaporation to modeled water loss 
values (computed from knowledge of the vegetational composition of homogeneous 
landscape units and their ecotones, and the functional response of these units 
to climatic forcing.

iii) To provide continuous tower fluxes of water, sensible heat, and CO2 in 
support of the development of Soil-Vegetation-Atmosphere-Transfer (SVAT) models 
at the stand and regional scales.
 
Data for this study were collected at two sites in the BOReal Ecosystem-
Atmosphere Study (BOREAS) Northern Study Area (NSA) at Thompson, Manitoba: a 
young jack pine forest (YJP), and a fen wetland.

1.4 Summary of Parameters

The following micrometeorological variables were measured at the YJP site: net 
radiation, incoming and reflected solar radiation, incoming and outgoing 
longwave radiation, incoming and reflected photosynthetic photon flux density 
(PPFD), wind speed, wind direction, wet- and dry-bulb temperature, biomass 
temperature, soil temperature, soil heat flux, sensible heat flux, latent heat 
flux, CO2 flux, rainfall, and soil moisture.

In addition, the following biophysical variables were measured: stomatal 
conductance, leaf temperature, leaf area index (LAI(, tree height (h), diameter 
at breast height (dbh), and tree stem density.

1.5 Discussion

Data collected for this study can be divided into two primary groups: 
micrometeorological measurements and biophysical measurements.

Micrometeorological Measurements

The primary objective of this project was to develop a full suite of radiation, 
energy, and CO2 flux measurements for the two flux tower sites.  At both towers, 
identical instrumentation was used for data collection. The measurement systems 
used can be briefly summarized as follows:

i) Radiation balance fluxes, including PPFD, were monitored using standard 
instrumentation mounted near the top of the flux towers.

ii) Soil heat flux (G) was measured using soil heat flux plates combined with 
calorimetric calculations of heat storage (see Sections 4.1 and 9.1).

iii) Convective fluxes of latent (LE) and sensible (H) heat were measured 
directly via the eddy covariance technique.

iv) Net CO2 flux (FeCO2) was measured using an eddy covariance system; this 
system consisted of a single-axis sonic anemometer and a fast-response infrared 
CO2 gas analyzer.  The air intake was located at the same level as the sonic 
anemometer, and air was drawn down to the gas analyzer at the base of the tower.  
Lag times between the gas analyzer signal and the sonic anemometer signal were 
included in the online processing of the flux; offline processing included heat 
flux density corrections (Webb et al., 1980) and CO2 storage in the air layer 
between the intake and the surface.

Flux data were supported with accompanying meteorological measurements.  At each 
site, profiles of wind speed, temperature, and humidity were measured in the 
lower boundary layer.  In addition, soil and biomass temperatures, wind 
direction, and rainfall were monitored.

Tower data at both sites were collected from 15-Aug to 31-Aug-1993.  In 1994, 
the YJP tower was operational almost continuously from 23-May to 30-Sep, and the 
fen tower was operational from 08-Apr to 23-Sep.  Before 01-Jun, only convective 
energy fluxes and the supporting profile data were measured at the fen to 
support an associated hydrological study of snowmelt in an adjoining basin 
during the Focused Field Campaign (FFC) from 12-Apr to 02-May.  CO2 flux data 
came online at the fen by 01-Jun-1994.  In 1995, only the fen was operational to 
support the continuation of the hydrological experiment; data were collected 
from the tower from 15-Apr to 10-Jun.  In 1996, the measurement period at the 
YJP extended from 08-May to 07-Nov; at the fen data were collected from 29-Apr 
to 05-Nov.

Biophysical Measurements

The micrometeorological data at YJP were supplemented with biophysical data 
collected from areas surrounding the tower.  These measurements included (h), 
(dbh), (LAI), and stomatal conductance of the coniferous overstory.  The 
measurements, combined with the tower data, represent the basis for intersite 
comparisons of surface-atmosphere interactions.

1.6 Related Data Sets

BOREAS AFM-07 SRC Surface Meteorological Data
BOREAS HYD-01 Volumetric Soil Moisture Data
BOREAS TF-10 NSA-Fen Tower Flux and Meteorological Data
BOREAS TF-04 SSA-YJP Tower Flux and Meteorological Data

2. Investigator(s)

2.1 Investigator(s) Name and Title

Dr. J. Harry McCaughey (Principal Investigator (PI) at YJP)
Department of Geography
Queen's University 

Dr. Dennis E. Jelinski (PI at Fen)
Department of Geography
Queen's University 

Two PIs were associated with the TF-10 group: Harry McCaughey and Dennis 
Jelinski.  Harry McCaughey oversaw the tower fluxes at both the YJP and the fen, 
and Dennis Jelinski was responsible for the vegetation work at the fen.  Peter 
Lafleur shared responsibility for measurements at both sites.  In addition, a 
large group of very competent graduate students, field assistants, and 
technicians contributed to the overall success of the work.  Special mention 
goes to David Joiner and Paul Bartlett (Queens University).  David developed 
and built the CO2 measurement system.  Paul started work as a technician in the 
group and later stayed at Queens as a doctoral student.  He made many 
contributions, but special mention must go to his work on assembling and 
organizing the deployment of equipment in 1993 and to his porometry work at the 
YJP site in 1994 and 1996.  Andrew Costello, Queens, helped in the field setup 
in 1993 and did most of the initial stand measurements on the YJP canopy.  He 
was assisted by Blair Mantha from Trent.  Bob Metcalfe, Queens and Trent, 
worked on an associated hydrology project focused upon the feeder basin north of 
the fen.  He was supervised jointly by Jim Buttle, Trent University, and Harry 
McCaughey.  Mike Skarupa and Greg Bryant, Trent, assisted in the data collection 
efforts at both sites.  Kristan Boudreau was an outstanding field assistant, and 
she performed excellent work in 1994 in all facets of the experiments at both 
sites.  Bruce Robertson and Derek Mueller were able field assistants in 1996.  
Finally, a special thanks to Laura Liblik, who did the majority of the work 
associated with the preparation of the data set before its submission to the 
BOREAS Information System (BORIS).  Her attention to detail, her writing, and 
her editorial skills are much appreciated. 

2.2 Title of Investigation 

Surface Energy and Water Balances of Forest and Wetland Subsystems in the Boreal 
Forest - Surface Atmosphere Links and Ecological Controls 

2.3 Contact Information                  

Contact 1
---------
Dr. J. Harry McCaughey
Dept. of Geography
Queen's University
Kingston, ON
CANADA
(613) 545-6035
(613) 545-6122 (fax)
mccaughe@post.queensu.ca

Contact 2
---------
Dr. Peter M. Lafleur
Dept. of Geography
Trent University
Peterborough, ON
CANADA
(705) 748-1487
(705) 748-1205 (fax)
plafleur@trentu.ca

Contact 3
---------
Dr. Dennis Jelinski
School of Environmental Studies
Queen's University
Kingston, Ontario
CANADA
(613) 545-6875
(613) 545-6617 (fax)
dj4@qsilver.queensu.ca

Contact 4
----------
K. Fred Huemmrich
University of Maryland
NASA GSFC
Greenbelt, MD  20771
(301) 286-4862
(301) 286-0239 (fax)
Karl.Huemmrich@gsfc.nasa.gov

3. Theory of Measurements

Many of the individual measurements made during the study involved routinely 
collected data obtained with a single instrument (e.g., incoming solar radiation 
and temperature measurement with thermocouples).  Such measurements represent 
standard data collection techniques, and specific, detailed elaboration is not 
provided in this report.  However, there is discussion of some limited aspects 
of these routine measurements where such detail is required for a complete 
understanding.  Readers are referred to the manufacturers' specifications for 
details on the theory of measurement and operation of individual instruments. 

The following section describes only the measurement method used for the fluxes.

Sensible (H) and latent (LE) heat fluxes and the net flux of CO2 (FeCO2) (net 
ecosystem exchange, NEE) were found using the eddy covariance technique 
(Campbell and Unsworth, 1979; Tanner et al., 1993).  Fluxes are computed as the 
time-averaged product of the fluctuations of vertical wind velocity (w') and 
fluctuations of the appropriate scalar (the covariance).  For example, 
fluctuations of temperatures (T') for H, water vapor density (q') for LE, and 
CO2 concentration (C') for FeCO2, give:

LE = L <w'q'>                                                (3.1)

H = rho Cp <w'T'                                             (3.2)

and FeCO2 = rho(c) <w'C'                                     (3.3)

where L is the latent heat of vaporization of water (J/kg), rho is the density 
of air (kg/m3), Cp is the specific heat of air at constant pressure (J/(kg C)), 
rho(c) is the density of CO2 (kg/m3), and the < > symbol  represents a time-
averaged product or covariance.

In practical terms, the eddy covariance technique is very sensitive to site 
conditions and instrument response.  For one-dimensional measurements, the site 
is assumed to be perfectly flat.  This eliminates net positive or negative 
horizontal advection.  Ideally, the response time of the instrument should be 
fast enough to monitor the complete spectrum of frequencies occurring in the 
turbulent flow.  However, the total response is determined by the response time 
of the individual sensor, the instrument size and orientation, and the capacity 
to monitor the signal.  Where two sensors are required, one to monitor w' and 
the other to monitor the appropriate scalar variable (T', q', or C'), then 
separation of the instruments in horizontal space introduces a possible error of 
mismatched frequencies sensed by the two systems.  It is desirable to have the 
instruments as close together as possible; however, this can result in 
distortion of the wind field of one instrument by the presence of the other.  A 
compromise is needed to overcome these two opposing problems, and sensors are 
typically placed 0.30 m to 0.40 m apart.  Given the current status of data 
logging capacity, eddy covariance instruments are usually sampled at a rate of 
10 Hz or greater.

4. Equipment 

4.1 Sensor/Instrument Description

Micrometeorological Instruments

Meteorological and flux data at both sites were collected with similar 
instrumentation. Instruments were mounted on towers as described in Section 
4.1.2.  A listing of instrumentation follows.

i) Net radiation was measured with a net pyrradiometer (model CN-1 Middleton, 
Carter-Scott Design, Victoria, Australia) aspirated with dry nitrogen gas.

ii) Incoming and outgoing solar radiation were measured with pyranometers (model 
8-48, Eppley Laboratories, Inc., Newport, RI, USA).

iii) Outgoing longwave radiation was measured with a pyrgeometer (model PIR, 
Eppley Laboratories, Inc., Newport, RI, USA). 

iv) Incoming and outgoing PPFD were measured with quantum sensors (model LI-
Q190SA, LI-COR, Inc., Lincoln, NE, USA).

v) Absolute wet- and dry-bulb temperatures were measured with psychrometers 
constructed from PVC tubing covered with reflective tape.  Ventilation was 
supplied by a 12-volt DC fan that gave an air flow between 4-6 m/s across the 
sensor.  The sensors were single-junction 24 a.w.g. copper-constantan 
thermocouples sealed with epoxy in stainless steel tubing (250 mm in length, 3.5 
mm in diameter).  The wet-bulbs were covered with cotton wicking to a length of 
150 mm.

vi) Wind speeds were measured with 3-cup anemometers (model 12102, R.M. Young 
Co., Traverse City, MI, USA).  The anemometers contain a DC generator that 
produces an analog signal proportional to wind speed. 

vii) Wind direction was measured with a vane (model 12302, R.M. Young Co., 
Traverse City, MI, USA) containing a potentiometer that designates direction as 
proportional to the voltage output.

viii) Rainfall was measured with tipping bucket gauges (YJP: model P501, 
Weathermeasure Corporation, Sacramento, CA, USA; Fen: model TE252M, Campbell 
Scientific, Inc., Logan, UT, USA).

ix) Soil temperatures were measured with single-junction copper-constantan 
thermocouples (24 a.w.g.) fixed into a 3.18-cm-diameter wooden dowel inserted 
into the soil.  Two soil temperature rods were installed at each site in order 
to sample soil temperatures below different cover types.

At YJP, one rod was placed 14 m from the tower at 323 among young jack pine 
trees 1.5 m in height.  In 1993, temperatures only from 1-, 5-, and 10-cm depths 
are available from the north site.  Temperatures from 1-, 5-, 10-, 25-, 50-, and 
75-cm depths are available from this site in 1994.  The second rod was placed 
6.7 m to the west of the tower (253) among trees 2-3 m in height.  Temperatures 
at the west site were recorded at depths of 1, 5, 10, 25, 50, 75, and 100 cm in 
both years.

x) Soil heat flux was measured at each site with two soil heat flux plates 
(model HFT-3, Radiation Energy Balance Systems, Inc. (REBS), Seattle, WA, USA).  
Values from these instruments, combined with the soil temperature profiles, were 
used to calculate soil heat flux at each site as follows.

At YJP, measurements were obtained at a depth of 10 cm below the soil surface.  
Heat storage in the soil layer above the heat flux plates was calculated using 
temperatures measured at the 1-cm, 5-cm and 10-cm levels (see Section 9.1).

xi) All tower variables (except eddy covariance) were recorded on data loggers 
(model CR7X, Campbell Scientific, Inc., Logan, UT, USA). The eddy covariance 
signals were recorded on data loggers (model 21X, Campbell Scientific, Inc., 
Logan, UT, USA).

xii) CO2 concentration and flux densities were measured with a system designed 
at Queen's University by D. Joiner.  It consisted of a single-axis sonic 
anemometer (mentioned above) and a fast response infrared gas analyzer (IRGA) 
(model LI-6252, LI-COR, Inc., Lincoln, NE, USA).

Air is drawn by an AC pump from the intake of a tube (1/4" i.d. Bev-a-line IV) 
situated on the sonic anemometer arm to the IRGA at the base of the tower.  The 
flow is split before reaching the IRGA, and the line to the IRGA passes through 
a fine particle filter.  Air from the IRGA passes a pressure transducer (model 
PX142, Omega Engineering, Stamford, CT, USA) and a mass flow sensor (model 
5860E, Brooks Instruments Division, Hatfield, PA, USA).

Cross-correlation analysis was used to determine the travel time of the air from 
the tube inlet to the gas analyzer.  The flux density of carbon dioxide was then 
determined with the eddy covariance technique by finding the covariance of the 
10-Hz direct output from the gas analyzer with time-lagged vertical wind 
velocity measured with a one-dimensional sonic anemometer (model CA-27, Campbell 
Scientific, Inc., Logan, UT, USA).

The direct output from the IRGA was calibrated once a day using calibration 
gases flowing through the gas analyzer at the same pressure as that of the air 
down the tower.  These field calibrations, linear over the range of ambient 
carbon dioxide concentrations and unchanging with temperature, were constantly 
corrected for pressure changes recorded with the gauge pressure transducer.

Data processing and storage were done on data loggers (model 21X, Campbell 
Scientific, Inc., Logan, UT, USA), using the covariance at 10 Hz data and a 15-
minute averaging subinterval.  The CO2 flux data were corrected for fluctuations 
of temperature and water vapor density during postseasonal analysis (Webb et al. 
1980).

Absolute concentrations of CO2 were calculated using the factory calibration 
equation supplied with the LI-6252 and were corrected for air pressure 
fluctuations.  Station values for air pressure were obtained from the Thompson 
airport and entered daily as a constant into the data loggers.  Daily field 
calibration of the IRGA showed that the absolute concentration may exhibit a 
drift of up to 3 ppmv over a 24-hour period.

Final CO2 flux density values combine the contributions from both the eddy flux 
and the changes in CO2 storage for the volume of air beneath the eddy covariance 
instruments.

Biophysical Instruments

i) Biomass temperatures at YJP were measured with copper-constantan parallel 
thermocouples (30 a.w.g.) embedded directly into the boles.  Thermojunctions 
were placed at the approximate center of the biomass volume (1/3 of the way up 
the tree and 1/3 of the radius into the boles) (McCaughey and Saxton, 1988; 
Saxton and McCaughey, 1988).  Four parallel thermocouples, each one consisting 
of three thermojunctions wired in parallel, were used.  One set was placed in 
three large trees (~5.0 m in height) 12.6 m from the tower at 185, the second 
set was placed in three medium trees (~2.5 m in height) 9.6 m from the tower at 
218, the third set was placed in three small trees (~1.5 m in height) 14 m from 
the tower at 230, and the fourth set was placed in three small trees (~1.5 m in 
height) near the northern soil heat flux plate at 323.

ii) Leaf stomatal conductance was measured with a steady state diffusion 
porometer (model LI-1600, LI-COR, Inc., Lincoln, NE, USA).  Measurements on jack 
pine shoots required that the sensing head was fitted with a cylindrical chamber 
(model LI-1600-07, LI-COR, Inc., Lincoln, NE, USA).

iii) Projected LAI was measured with an optical Plant Canopy Analyzer (model 
LAI-2000, LI-COR, Inc., Lincoln, NE, USA).

4.1.1 Collection Environment

The instruments were operated mainly under summer conditions with maximum 
temperatures around 35 C.  Data were collected over the growing season of 1994 
and the spring through fall/winter of 1996.  In the spring and fall/winter 
seasons, more extreme low temperatures were experienced.  During these periods, 
the environment was more severe, and freezing temperatures were common; the 
lowest temperatures experienced were around -30 C.

4.1.2  Source/Platform

The towers erected at YJP and fen were 12-meter-tall triangular communications 
type, guyed on three sides, and anchored into the mineral soil.  At both sites, 
all sensors were mounted on the towers with fixed aluminum (3.18 cm diameter) 
extension arms, with the exception of the eddy covariance equipment, which was 
mounted on a swivel system allowing for orientation of the instruments into the 
wind.  Sensor height above the surface, distance from the tower, and orientation 
(degrees from magnetic north) are given for the YJP in Table 1.

Biomass temperatures were measured at two sites in the vicinity of the flux 
tower at YJP.  One site, directly west of the tower, was named the west 
site, and the other, located north of the tower, was named the north site.  
Biomass temperature sensors consisted of three-junction parallel thermocouples, 
and one thermojunction was inserted into three separate trees in three chosen 
height categories (small, medium, and large) at the west site.  At the north 
site, only small trees existed.  Each thermojunction was inserted into the bole 
to a depth of one-third the radius depth at a height of one-third the height of 
the tree (see Section 4.1).  Table 2 shows the height and dbh for all trees 
sampled at the two measurement sites.

Table 1. Sensor heights on the flux tower at the YJP in 1993, 1994, and 1996.  
The orientation of the arm holding the sensor is given in degrees measured from 
magnetic north, and the distance (m) from the tower is given.  The symbol n/a, 
indicating not applicable, means that no measurements were taken.  The 
orientation of the arm holding the sonic anemometer and the krypton hygrometer 
was variable on a swivel mount that could be set anywhere from 120 from 
magnetic north through 360 to 25 from magnetic north.

Variable/                     Height(m)     Distance(m) Orientation
 Sensor             1993    1994    1996                (degrees)

incoming solar
radiation/         11.82   11.82   11.82      1.5           143
pyranometer

outgoing solar
radiation/         11.58   11.58   11.58      1.5           143
pyranometer

outgoing longwave  11.38   11.38   11.38      1.5           203
radiation/
pyrgeometer

net radiation/     11.70   11.70   11.70      2.3           133
net pyrradiometer

incoming PPFD/     11.54   11.54   11.54      1.5           213
quantum sensor

outgoing PPFD/     11.36   11.36   11.36      1.5           213
quantum sensor

wet- and dry-bulb
temperatures/
thermocouples

    Canopy          1.60    1.60    n/a       1.5           233
    Level 1         5.10    5.17    5.17      0.8           233
    Level 2         6.10    6.10    n/a       0.8           233
    Level 3         7.10    7.15    n/a       0.8           233
    Level 4         9.10    7.70    7.70      0.8           233
    Level 5        11.10   10.30   10.30      0.8           233

wind direction/    11.10   10.30   10.30      1.8           323 
vane

wind speed/
cup anemometer

    Level 1         5.10    5.17    5.17      1.5           323
    Level 2         6.10    6.10    n/a       1.5           323
    Level 3         7.10    7.15    n/a       1.5           323
    Level 4         9.10    7.70    7.70      1.5           323
    Level 5        11.10   10.30   10.30      1.5           323

vertical wind 
speed/              9.35    9.00    9.00      1.0       120-360-25
sonic anemometer

vapor density/
krypton             9.35    9.00    9.00      1.0       120-360-25
hygrometer

relative humidity
T/RH sensor         n/a     n/a    10.30      0.2           232
                                         

Table 2. Location of biomass temperature sensors at the west and north 
measurement sites at YJP.  The same locations were used in all three 
experimental years: 1993, 1994, and 1996. h is tree height (m) and dbh (m) is 
the diameter at breast height.  At the west site, three sizes of trees were 
sampled: small, medium, and large.  Three trees in each size range were sampled 
with three-junction parallel thermocouples, and one thermojunction was located 
in each tree.

                    h(m)    dbh(m)

  West site:

    small trees     1.45    0.0045
                    1.20   <0.0030
                    1.75    0.0070

    medium trees    2.70    0.0210
                    2.35    0.0160
                    2.90    0.0190

    large trees     5.80    0.0600
                    4.20    0.0420
                    4.30    0.0430

  North site:

    small trees     1.75    0.0120
                    1.72    0.0088
                    0.97   <0.0030 

4.1.3 Source/Platform Mission Objectives

The primary objective of the team was to collect and analyze the 
micrometeorological data from the two flux towers on a continuous basis during 
all of the experiments. In addition, data were assembled to characterize the 
surfaces state in terms of LAI, type, distribution, height, and density of the 
vegetation, and stomatal conductance at the YJP only.  Subsidiary experiments in 
1996 at the YJP measured soil evaporation, throughfall, and rainfall 
interception of the canopy. 

4.1.4 Key Variables

The key meteorological variables are incoming and reflected solar radiation, 
PPFD, outgoing terrestrial radiation, net radiation, wet- and dry-bulb 
temperatures, wind speed, wind direction, latent and sensible heat fluxes, net 
CO2 flux, soil temperature, biomass temperature, rainfall, and water level.  The 
key biophysical variables are LAI, leaf stomatal conductance, h, stem density, 
and dbh.

4.1.5 Principles of Operation

Sonic Anemometer

The sonic anemometer system (model CA27, Campbell Scientific ,Inc., Logan, UT, 
USA) obtains the velocity fluctuations of vertical wind speed from the measured 
Doppler shift induced by the wind velocity on an ultrasonic frequency pulse 
broadcast across a 10-cm path.  The effect of temperature on sound velocity is 
eliminated by determining the Doppler frequency from the difference between 
forward and reverse path observations.  Electronic processing of the signals 
from the ultrasonic transducers produces a real-time analog output voltage in 
the range 4.0 V DC.

Air temperature fluctuations for the Campbell Scientific eddy covariance system 
are measured with a fine-wire thermocouple mounted about 4 cm from the 
anemometer sound path.  The thermocouple output is amplified to a 4.0 V DC 
signal.  The thermocouple temperature is referenced to the instrument case, 
which is thermally lagged and responds slowly to temperature changes.

Absorption Hygrometer

The absorption hygrometer (model KH20, Campbell Scientific, Inc., Logan, UT, 
USA) measures the ultraviolet light transmission across a nominal 1-cm path in a 
water vapor absorption band corresponding to a krypton emission line (Campbell 
and Tanner, 1985).  Instrument response is at least sufficient to resolve 
fluctuations of 80 Hz.  The instrument output is a voltage in the range 0 to 4 V 
DC.  The signal strength may be subject to gradual diminution as a result of 
scale accumulation on the optical surfaces.

Longwave Radiation Measurement

The sensing surface of a pyrgeometer (model PIR, Eppley Laboratories, Inc., 
Newport, RI, USA) consists of a differential thermopile that measures net 
longwave radiation fluxes between itself and the sky or ground (depending on 
orientation).  The dome of the pyrgeometer is composed of silicon with a vacuum-
deposited interference filter on its inner surface.  The composite dome 
transmission shows an abrupt transition between approximately 3 and 4 
micrometers from complete opaqueness to maximum transparency.

The outgoing longwave radiation from the instrument is calculated using the 
temperature of its blackbody cavity and the Stefan-Boltzmann equation.  This 
flux is added to the thermopile signal to get the total incoming flux.  The 
temperature of the blackbody radiator can be measured using a thermistor.
 
The thermopile output signal is measured as a single-ended voltage in the 
Campbell Scientific CR7X data logger.  The case thermistor is not polarized, and 
is connected between an analog input channel and ground.  A 1000-ohm resistor is 
connected between the analog input channel and a switched analog output channel 
(725 card).  The thermistor is excited with 1350 mV across the 1000-ohm 
resistor, and the thermistor (pyrgeometer) temperature is calculated as a 
function of the thermistor voltage (a function of its resistance).  This method 
corresponds to the protocol for using the Eppley pyrgeometer proposed by the 
National Atmospheric Radiation Center (NARC).  This method does not use the 
pyrgeometer's battery-powered temperature compensation circuit, and no battery 
should be installed when using the pyrgeometer in this manner.

Plant Canopy Analyzer

The plant canopy analyzer (model LAI-2000, LI-COR, Inc., Lincoln, NE, USA) is 
composed of a LAI-2070 control unit and a LAI-2050 sensor head.  The sensor head 
projects the image of its nearly hemispheric view onto five detectors arranged 
in concentric rings (approximately 0-13, 16-28, 32-43, 47-58, and 61-74 degrees 
of zenith angle).  Radiation above 490 nm is rejected.  Data are stored and 
processed in the control unit.  LAI is calculated by the reduction in light 
intensity measured between an above-canopy reading and a below-canopy reading.  
Normally, simultaneous measurements of these two quantities can be achieved with 
two sensors connected to the same control unit.  Where this is not possible, two 
sensors and separate control units can be used and the data later integrated, or 
a single sensor and control unit is used for above- and below-canopy 
measurements.  The LAI value obtained from the LAI-2000 relates directly to 
projected leaf area; corrections can be applied for clumping within the canopy 
or conversion to total surface area.  For further information, consult the LAI-
2000 plant canopy analyzer instruction manual.

Diffusion Porometer

Leaf stomatal conductance was measured with a steady state porometer (model LI-
1600, LI-COR, Inc., Lincoln, NE, USA).  Leaf samples are placed in contact with 
a cuvette by clamping a portion of the leaf over an aperture in the cuvette 
wall.  The relative humidity in the cuvette is held constant by flowing dry air 
directly into the cuvette at an appropriate rate.

Diffusive resistance/conductance is determined by measuring the flow required to 
obtain a balance between the flux of water transpired from the leaf and the flow 
of moist air out of the cuvette at a set humidity (usually ambient).  The 
instrument also measures leaf temperature, cuvette temperature, and 
transpiration rate.  For measurements of coniferous needles, the LI-1600-07 
cylindrical chamber is used.  This allows a small portion of a branch containing 
needles to be inserted into the cuvette.  The LI-1600 is also outfitted with a 
quantum sensor for instantaneous measurement of PPFD.

4.1.6 Sensor/Instrument Measurement Geometry

See Table 2 in Section 4.1.2.

4.1.7 Manufacturer of Sensor/Instrument

Mass flow sensor and control unit for eddy covariance system:
Brooks Instruments Division
Emmerson Electric Co.
407 W. Vine St.
Hatfield, PA 19440
USA
(215) 362-3500

Sonic anemometer; krypton hygrometer; fine-wire thermocouple; CR7X and 21X data 
loggers; rain gauge (fen):
Campbell Scientific, Inc.
P.O. Box 551
Logan, UT 84321
USA
(519) 354-7356

Pyranometer; pyrgeometer:
Eppley Laboratories, Inc.
P.O. Box 419
Newport, RI 02840
USA
(401) 847-1020

LAI-2000 Plant canopy analyzer; diffusion porometer; quantum sensor; CO2 
infrared gas analyzer:
LI-COR, Inc.
4421 Superior Street
P.O. Box 4425
Lincoln, NE 68504
USA
(402) 467-3576

Net pyrradiometer:
Carter-Scott Design
22 Ailsa Street
Box Hill
Victoria, 3128
AUSTRALIA
+61-3-9899-4277

Pressure transducer; thermocouple wire:
Omega Engineering
One Omega Drive
P.O. Box 4047
Stamford, CT 06907
USA
(203) 359-1660

Soil heat flux plate:

REBS
P.O. Box 15512
Seattle, WA 98115-0512
USA
(206) 624-7221

Cup anemometer; wind vane:
R.M. Young Co.
2801 Aero Park Drive
Traverse City, MI 49648
USA
(616) 946-3980

Rain gauge (YJP):
Weathermeasure Corporation
P.O. Box 41257
Sacramento, CA 95841
USA
(916) 481-7565

All other instruments were produced in the climate laboratories at either 
Queens University or Trent University.

4.2 Calibration

Pyranometers, pyrgeometers, and net pyrradiometers used at both sites were 
calibrated at NARC, Atmospheric Environment Service (AES), Downsview, Ontario. 
Following the intersite calibration on net pyrradiometers performed in the field 
in 1994 with the roving REBS 6-net pyrradiometer (Hodges and Smith, 1997; Smith 
et al., 1997), a corrected set of net radiation data was calculated for the 
1994, 1995, and 1996 experimental periods for both the fen and YJP.  The 
corrected net radiation data will potentially facilitate the intercomparison of 
flux behavior between the tower flux sites.

CO2 concentrations for high- and low-span calibration gases were determined at 
the Carbon Cycle Research Section, AES, Downsview, Ontario, Canada.

Factory calibrations were used for several instruments, and the recalibration 
details for individual sensors are given below.

The details of the recalibration performed on the porometers (LI-COR, Inc., 
Lincoln, NE, USA) used in the experiments are given in Section 4.2.2.

Following the 1993 field experiment, each individual calibration for the group 
of cup anemometers and wind vane (R.M. Young Co., Traverse City, MI, USA) was 
checked using the wind tunnel at Trent University, and no changes were needed to 
the original factory calibrations.  Because the potentiometers on the two wind 
vanes were set in the field each time the instruments were deployed, both can be 
considered to have had regular field calibration checks.

For the soil heat flux plates (REBS, Seattle, WA, USA), the factory calibrations 
were accepted for all four transducers, two at each site.

Routine calibration checks were done on all rain gauges (Campbell Scientific 
Inc., Logan, UT, USA and Weathermeasure Corporation, Sacramento, CA, USA) by 
pouring a known amount of water into the gauge and noting the response. In all 
cases, the gauges were within the manufacturers specification.

The sonic anemometers and krypton hygrometers (Campbell Scientific, Inc., Logan, 
UT, USA) at both the fen and YJP sites were recalibrated in March 1994 following 
the 1993 experiment and before redeployment for the 1994 experiment. Minor 
changes resulted, but they were not large enough to require correction to the 
1993 data.

For all thermocouples, the appropriate calibration equation available in the 
data loggers (Campbell Scientific, Inc., Logan, UT, USA) was used.

4.2.1 Specifications

Whenever a new calibration was determined for an instrument, the new calibration 
was applied from the time of the recalibration.  There was no attempt to blend 
the calibrations before and after the recalibration.  Any step-up or step-down 
in the data values as a result of recalibration was accepted.  For all 
instruments, the calibration changes were minor, and there were no instances 
where a blending of the calibrations was necessary.

4.2.1.1 Tolerance

The precision of the measured meteorological variables and the corresponding 
transducers are summarized below.  In the following list, micromole is 
abbreviated to umol.

Variable                Transducer              Precision
________________________________________________________________________

solar radiation         Eppley pyranometer      1 W/m2
longwave radiation      Eppley pyrgeometer      1 W/m2
net radiation           Middleton net
                          pyrradiometer         1 W/m2
PPFD                    LI-COR quantum sensor   1 umol/(m2 s1)
carbon dioxide 
  concentration         LI-COR IRGA             1 ppmv
soil heat flux          REBS heat flux plate    1 W/m2
air, soil, and
 biomass temperature    Copper/constantan
                          thermocouple          0.1 C
horizontal wind speed   R.M. Young cup
                          anemometer            0.1 m/s
wind direction          R.M. Young wind vane    1
relative humidity       R.M. Young T/RH sensor  1%
vertical wind speed     Campbell Scientific
                          sonic anemometer      0.1 m/s
rainfall                Campbell Scientific
                          tipping bucket        0.1 mm
rainfall                Weathermeasure
                          tipping bucket        0.254 mm

4.2.2 Frequency of Calibration

All radiometers used in the study were on a regular, 2-year calibration cycle.  
This calibration frequency was increased during BOREAS, and each radiometer was 
calibrated before each major field experiment.  Full calibrations were done in 
April 1994, October 1994, and March 1996.

One sonic anemometer (model CA27, Campbell Scientific, Inc., Logan, UT, USA) was 
recalibrated by the manufacturer in May 1995 following water damage to the 
instrument in September 1994 at the fen.

Two porometers (model 1600, LI-COR, Inc., Lincoln, NE, USA) were used in the 
study.  Each one was calibrated by the manufacturer prior to the 1993 field 
experiment; they were aslo intercalibrated.  The single one that continued to be 
used in 1996 at the YJP was recalibrated by the manufacturer in April 1995.

The krypton hygrometers from the YJP and fen were calibrated in 1993 before 
deployment in the field and were recalibrated in March 1994.

Calibrations were determined on all CO2 reference gas tanks prior to both major 
field seasons in March 1994 and March 1996.

Routine calibration checks were made on the rain gauges, following the protocol 
suggested by the manufacturers, prior to their deployment in all field 
experiments.  No calibration change was necessary to either gauge.

4.2.3 Other Calibration Information

A summary follows of the instruments used at each site along with their 
calibration histories.

Solar radiation was measured using Eppley pyranometers. The instruments, 
identified by serial number, used at both sites for each experiment are given in 
Table 3.

Table 3. Eppley pyranometers used at the YJP and Fen in all experimental years. 
Each pyranometer is identified by its serial number.

Site: YJP
                              Year
            1993        1994        1995        1996
Variable    -----       -----       -----       -----
      Kd    13762       15889       ------      15889
      Ku    13855       14713       ------      14713

The calibration histories of the pyranometers are shown in Table 4.  All 
calibrations remained stable through the BOREAS field periods, and the largest 
change in any calibration was -0.57%.

Table 4. Calibration history of the Eppley pyranometers used in all experimental 
years.  The change in calibration is given as a percentage from the previous 
value.  The units of calibration are microvolts/(W1 m2).

Serial
number      Year       Calibration        %change in calibration 
13762       1992        12.21              -1.12
            1994        12.14              -0.57
            1996        12.20               0.49

13855       1992        10.92              -0.55
            1994        10.89              -0.27
            1996        10.92               0.28

14713       1992        11.17              -0.62
            1994        11.14              -0.27
            1996        11.14               0.00

15889       1992        11.09              -1.10
            1994        11.05              -0.36
            1996        11.06               0.09

Longwave radiation was measured using Eppley pyrgeometers.  Instrument 20837F3 
was used at YJP in 1993, 1994, and 1996, and instrument 29583F3 was used at Fen 
from 1993 to 1996.  The calibration history of each instrument is given in Table 
5.  The first calibration of instrument 29583F3 in 1994 proved to be wrong 
because of a malfunctioning reference temperature bath NARC.  This was corrected 
by a recalibration of the instrument the same year, and all of the data were 
corrected in postprocessing.

Table 5. Calibration history of the Eppley pyrgeometers used in all experimental 
years.  The change in calibration is given as a percentage from the previous 
value.  The units of calibration are microvolts/(W1 m2).

Serial
number            Year      Calibration   %change in calibration
20837F3           1992        3.96        -2.22
                  1994        3.88        -2.02
                  1996        3.86

29583F3           1993        3.97
                  1994        3.62        -8.82 (calibration is suspect)
                  1994        3.83        -3.53 (recalibration for 1994)
                  1996        3.83         0.00

Net radiation was measured using Middleton net pyrradiometers. The instruments 
used are listed in Table 6.

Table 6. Middleton net pyrradiometers used in the field experiments. Each 
instrument is identified by serial number.

Serial
number      Site
 1330       Fen in 1993, and from DOY 97-145 in 1996 
 1333       Fen in 1994, and 1995, and from DOY 146 in 1996
 1408       YJP in 1993, 1994, and 1996

The calibration histories of the net pyrradiometers are given in Table 7.  For 
all net pyrradiometers, the calibration values are given separately for 
shortwave (SW), longwave (LW), and combined - the arithmetic average of SW and 
LW.  The combined value was used for all times of the day, including the 
nighttime, when only longwave radiation is present.  All instruments had two 
calibrations in 1994.  The first calibration proved to be wrong because of a 
malfunctioning reference temperature bath at NARC.  This was corrected by a 
recalibration of the instrument the same year, and all of the data were 
corrected in postprocessing.  With the exception of the aberrant first 
calibration in 1994, all instruments remained stable for the duration of the 
experiments; the largest change was less than 4% and was normally less than 1%.

Table 7. Calibration history of the Middleton net pyrradiometers used in all 
experimental years.  The change in calibration is given as a percentage from the 
previous value. The units of calibration are microvolts/(W1 m2). Separate 
calibrations are given for shortwave (SW), longwave (LW), and combined  the 
arithmetic average of the SW and LW values. The calibration constant (cal. 
constant) is the ratio of the SW to LW calibration.

Serial                 % change        % change            % change   cal.
number   Year   SW        SW       LW     LW     combined  combined constant
1330     1992  37.52    -0.87    35.18  -3.98     36.35    -2.42    1.07
         1994  38.16     1.17    32.40  -7.90     35.28    -2.94    1.18
         1994  37.55     0.08    34.82  -1.02     36.19    -0.44    1.08
         1996  35.54    -5.35    34.13  -1.98     34.84    -3.73    1.04

1333     1992  37.74    -2.15    34.90  -6.46     36.32    -4.27    1.08
         1994  38.41     1.78    32.85  -5.87     35.63    -1.90    1.17
         1994  38.17     1.14    34.62  -0.80     36.39     0.22    1.10
         1996  38.12    -0.13    35.17   1.59     36.64     0.69    1.08

1408     1992  38.58    -1.36    35.99  -5.01     37.28    -3.14    1.07
         1994  38.53    -0.13    35.83  -0.44     37.18    -0.29    1.08
         1996  38.17    -0.93    35.36  -1.30     36.77    -1.10    1.08

PPFD was measured using LI-COR, Inc. quantum sensors.  Table 8 shows the 
instruments used at each site in each experimental year, and Table 9 gives the 
calibration constants.

Table 8. Quantum sensors used at the experimental sites and the variables 
measured: PPFDd is incoming PPFD, and PPFDu is reflected PPFD.  Instruments are 
identified by serial number.

Serial
number            Site                       Variable
Q17605            Fen 1993 to 1996            PPFDd
Q16754            Fen 1993 to 1996            PPFDu
Q17614            YJP 1993, 1994, 1996        PPFDd
Q17613            YJP 1993, 1994, 1996        PPFDu

Table 9. Calibration constants in units of (micromole/(s1 m2))/mv for the 
quantum sensors used in the experiments.  The instruments are identified by 
serial number.

Serial      Calibration
Q17613      295.12
Q17614      307.74
Q17605      293.25
Q16754      355.87

CO2 concentration and CO2 flux density were measured using an IRGA (model LI-
6252, LI-COR, Inc., Lincoln, NE, USA) and a sonic anemometer (model CA27, 
Campbell Scientific, Inc., Logan, UT, USA).  Table 10 lists the IRGAs and the 
sonic anemometers used at both sites.  Sonic 1353 was damaged by water seeping 
into the lower arm at the conclusion of the 1994 experiment.  This instrument 
was repaired and recalibrated before being deployed again in 1996.

Table 10. The sonic anemometers and IRGAs used at the fen and YJP.  The 
instruments are identified by serial number. There was no CO2 flux measured at 
the fen in 1995; the sonic measured the convective fluxes only.

                      Serial
                      number         Site
Sonic anemometer      1201           Fen in 1995, YJP in 1993, 1994, and 1996
                      1353           Fen in 1993, 1994, and 1996
IRGA                  IRG2-208       Fen in 1993, 1994, and 1996
                      IRG2-209       YJP in 1993, 1994, and 1996

Soil heat flux was measured using REBS soil heat flux plates.  The calibrations 
of the plates and the sites where they were deployed are given in Table 11.

Table 11. Calibrations for the soil heat flux plates, in units of (W/m2)/mV, and 
the sites where they were deployed.  Individual plates are identified by serial 
number.

Serial number     Calibration      Site
   933060          40.0            Fen in 1993, 1994, 1995, and 1996
   933061          38.7            Fen in 1993, 1994, 1995, and 1996
   933062          39.0            YJP in 1993, 1994, and 1996
   933063          40.7            YJP in 1993, 1994, and 1996

Horizontal wind speed was measured using 3 cup anemometers (model 12102, R.M. 
Young Co., Traverse City, MI, USA).  These instruments have calibrations in 
units of mv at 1800 rpm, and this is combined with a second general calibration 
equation to convert rpm to m/s.  The calibrations of the anemometers are given 
in Table 12.

Table 12. Calibration of the 3-cup anemometers used at each site for horizontal 
wind speed measurement at the levels identified, e.g. U1 is the anemometer at 
level 1.  The units of the calibration are mv at 1800 rpm.

Site: YJP
                        Year
Level       1993        1994        1996
U1          2400        2400        2400
U2          2398        2398        -----
U3          2404        2404        -----
U4          2404        2404        2404
U5          2402        2402        2402

Site: Fen
                        Year
Level       1993        1994        1995        1996
U1          2400        2400        2400        -----
U2          2397        2397        2397        2397
U3          2396        2396        2401        2395
U4          2401        2401        2401        -----
U5          2399        2399        2399        2401

Relative humidity was measured using a combination temperature/relative humidity 
probe (model 41372VC, R.M. Young Co., Traverse City, MI, USA) at each site in 
1996 (Table 13).  The temperature is measured with an RTD sensor, and the 
relative humidity is measured with a capacitance element.  This probe was 
ventilated naturally and shielded by a 12-level plate shield.  Each probe has 
the same calibration and specifications (Table 14).

Table 13. Temperature/relative humidity sensors used at the sites in 1996.

Model       Serial number     Site
41372VC     1762              Fen
41372VC     1763              YJP

Table 14. Calibration and specifications for the temperature/relative humidity 
sensor (model 41372VC, R.M. Young Co., Traverse City, MI, USA).

Relative humidity:   operating temperature:  -10 C to 60 C
                     measuring range: 0 to 100%
                     accuracy at 20 C: 2% from 0-90% RH
                                        3% from 90-100% RH
                     stability: better than + or - 2% RH for 2 years
                     response time: 15 sec
                     sensor element: Vaisala intercap
                     output signal: 0-1 volt DC

Temperature:         calibrated measuring range: -50 C to 50 C
                     accuracy at 20 C: + or - 0.3 C
                     output signal: 0-1 volt DC

Rainfall was measured using tipping bucket rain gauges at both sites in all 
years. At the YJP, the gauge (model P510, Weathermeasure Corporation, 
Sacramento, CA, USA) was mounted at canopy top, and at the fen, the gauge (model 
TE525, Texas Instruments, supplied by Campbell Scientific, Inc., Logan, UT, USA) 
was at a height of one meter above the surface.  For the Weathermeasure gauge, 1 
tip equals 0.01 inches (0.254 mm of rain), and for the Texas Instruments gauge, 
1 tip equals 1 mm of rain.

Leaf stomatal conductance was measured using a steady-state diffusion porometer 
(model LI-1600, serial number SSP1094,  LI-COR, Inc., Lincoln, NE, USA).  The 
onboard quantum sensor (serial number Q11174) has a calibration constant of 5.21 
microamps/(1000 micromoles s1 m2).  This calibration remained stable from 1993 
to the end of the experiment in 1996; there was no change at the 1995 
recalibration.

Atmospheric pressure was measured at each site in 1996 using a Vaisala pressure 
transmitter (model PTB 101B, Vaisala, Oy, Finland, and supplied by Campbell 
Scientific, Inc., Logan, UT, USA).  Each instrument had been calibrated against 
a working standard in February 1996.  The instrument at YJP was S/N R0940044, 
and that at the fen was S/N R0940004.

5. Data Acquisition Methods

The outputs from all instruments producing voltages were recorded on data 
loggers.  Data from the loggers' memories were downloaded at regular intervals 
to either cassette tape or electronic storage module, and all data were 
transferred in the field to microcomputers and backed up on either floppy 
diskette or 1-GB Jaz drives (Iomega Corporation, Fenton, MO, USA).

Specific details for each major system are given below.

i) Tower data (except eddy covariance).   All signals were recorded on data 
loggers (model CR7X, Campbell Scientific Inc., Logan, UT, USA) at a scan rate of 
once per 10 seconds.  Output was processed every 3, 15, and 30 minutes depending 
on the variable.  Only 30-minute data are reported in the BORIS data base.

ii) Eddy covariance. All signals were recorded on data loggers (model 21X, 
Campbell Scientific, Inc., Logan, UT, USA) at a scan rate of once per 0.1 
seconds.  Intermediate processing was done every 15 minutes and output data were 
processed every 30 minutes.

iii) Leaf conductance. Porometric data from the LI-1600 were recorded on 
cassette tapes and later downloaded to microcomputers.  The measurement 
frequency was variable.  Data were collected on selected days under chosen 
weather conditions and only when the canopy was dry.  Typically, measurements 
started early in the morning and continued every hour until evening. 

iv) Forest canopy measurements. Canopy parameters (dbh, h, stem density) were 
recorded manually in field notebooks and later transposed to digital files.

6. Observations

6.1 Data Notes

Biophysical Measurements

The micrometeorological data at YJP were supplemented with biophysical data 
collected from areas surrounding the tower.  These measurements included h, dbh, 
LAI, and stomatal conductance of the coniferous overstory.  The measurements, 
combined with the tower data, represent the basis for intersite comparisons of 
surface-atmosphere interactions.  The sections below include descriptions of the 
major sampling programs.

i) Forest stand parameters were measured along transects within the zone 
designated as the wind aligned blob (WAB), the area of the site, centered on the 
experimental tower and of radius 500 m, within which the majority of the surface 
fluxes originate.  There was no sampling in the zone from 60 to 120.  The 
parameters measured included h, dbh, and stem density.  Five transects were 
sampled in both 1993 and 1994.  In 1993, each transect radiated a distance of 
500 m from the tower to the edge of the WAB at orientations of 10, 130, 190, 
250, and 310.  In 1994, the transects started at a distance of 125 m from the 
tower and continued out to 500 m at bearings of 40, 160, 220, 280, and 340, 
which are midday between the orientations of the earlier lines.  Two sampling 
methods were employed.  First, in 1993, tree density and height were measured in 
square, 25 m2 plots every 100 m along each transect.  A total of 20 plots were 
measured, and these data were designated as quadrat data.  Tree height was 
measured with a survey stadia rod or tape, and dbh for trees with h greater than 
1.3 m was measured with calipers.  Using a subsample of 312 trees, a 
relationship was found between dbh and h.  This relationship was then used to 
calculate tree heights for all trees sampled subsequently along the transects.  
The results of the quadrat survey indicated significant variation in stand 
parameters between transects and within a single transect.  For example, stem 
density varied from 8,000 to 11,000 trees/ha within the 20 sample plots.  To 
investigate smaller-scale spatial variation, a denser sampling was conducted by 
measuring dbh and stem density every 10 m along all transects using the Point 
Center Quarter Method (PCQM)(Mueller-Dombois and Ellenberg, 1974).  Trees with h 
>1.3 m and trees with h < 1.3 m were sampled separately.  A summary of the 1993 
PCQM transect data is shown in Table 15.  Aggregating these data revealed that 
the greatest stem density occurred within 200 m of the tower at a value of 
20,000 trees/ha, and a decrease out to the edge of the WAB where the value 
dropped to around 10,000 trees/ha.  The variation in stem density was associated 
with three vegetation patterns: dense cover of short trees, sparse cover of tall 
trees, and a mixture of short and long trees.  The average tree height on the 
site was 2.27 m.  Destructive sampling of nine trees yielded a value for the 
total green biomass of the canopy of 2.24 kg m-2 using the model developed by 
Alemdag (1983).

Table 15. Average canopy parameters for the YJP site developed from PCQM data 
from five transects sampled in 1993.  Each transect ran from the tower to the 
edge of the WAB, and samples were taken every 10 m.  The orientation of the 
transects is from magnetic north.  Units of measurement are as follows: dbh in 
cm, height in m, and stem density in trees/ha. Source: Costello (1995).

Transect          10          130         190         250         310
orientation
(degrees)

      dbh         1.39        1.77        1.51        2.05        1.60

      Tree
      height      2.08        2.35        2.17        2.55        2.23

      Stem 
      density     16800       14400       7000        13200       10000

      Number of
      samples     200         88          168         196         200

ii) Stomatal conductance was measured with a steady-state diffusion porometer 
(model LI-1600, LI-COR, Inc., Lincoln, NE, USA) fitted with a cylindrical 
chamber aperture.  Shoot samples were prepared at least 24 hours prior to the 
first measurements.  Preparation involved isolating a clump of needles that 
would fit completely into the porometers sample chamber.  To achieve this, some 
needles were removed from the twig on either side of the sample clump.  The bare 
twig, thus exposed, allowed the soft foam of the sample chamber to close around 
it and provided an air-tight seal around the sample clump.

After the needles were removed, the shoots were given 24 hours for sap to close 
over the scars.  The sample needle clump was tagged for identification.  
Following several measurement sessions (generally over a few weeks), the tagged 
needles were collected, counted, and bagged for later determination of needle 
areas.

The true leaf surface area of each needle was calculated using the volume 
displacement technique described by Brand (1987).  The true sample area was then 
used to correct the porometer conductance values as described in the porometers 
manual.

1993 Experiment

Sampling in 1993 was designed to investigate the variability of stomatal 
conductance in the YJP forest within the tower WAB.  Measurements were 
stratified according to needle age, position in the tree, and location in the 
forest.  These subcanopies were selected to be representative of the range of 
canopy morphologies (tree height and spacing) within the WAB as determined from 
the analysis of tree size distribution (described above).  The mean values of 
the three canopy parameters are summarized for each subcanopy below, where n/a 
means not applicable:

Sub canopy     dbh (cm)       h (m)     stem density (trees/ha)
--------------------------------------------------------------
      1           n/a         1.2               63000
      2           3.65        3.7               8000
      3           2.02        2.5               18000
      4           n/a         1.2               78000
      5           3.39        3.5               7000
      6           1.96        2.5               15000

Three canopy parameters are encoded in the variable CANOPY_ID, a three-digit 
number.  The first (left-most) digit of CANOPY_ID represents location in the 
forest.  This single digit ranges from 1 to 6, representing six different 
locations or subcanopies within the WAB.  The second digit represents needle age 
classification.  A 0 represents current year needles, and a 1 represents all 
needles aged 1 year and greater.  Finally, the third (right-most) digit 
represents position on the tree.  This digit ranges from 0 to 3.  A 0 represents 
breast height measurements regardless of subcanopy location.  Digits of 1, 2, 
and 3 represent other height positions that are dependent upon subcanopy.  For 
the small tree height canopies (locations 1 and 4), breast height was 
effectively the top of the trees.  Thus, a position indicator of 1 represents a 
measurement of approximately 2/3 of the tree height down from the top of the 
canopy.  In the taller canopies (locations 2, 3, 5, and 6), breast height 
represented the lowest position in the tree that was sampled.  A position 
indicator of 2 represents approximately 1/2 to 2/3 the height of the tree from 
the ground.  A position indicator of 3 indicates a measurement near the top of 
the canopy.

All porometry data are presented as the means from each porometry session.  
Sessions lasted between 15 and 30 minutes, and one to five sessions occurred on 
a given day.

1994 Experiment

At the conclusion of the experiment in 1993, the porometer was recalibrated and 
used again in 1994.

Aexamination of  the 1993 conductance data set revealed no significant 
differences between the numerous categories.  Therefore, it was decided that the 
measurement strategy should be simplified for 1994.  Two areas were selected for 
sampling.  The first, roughly 20 m x 20 m in size, was located 150 m from the 
flux tower at a bearing of 56; it was considered to be representative of the 
majority of the site that was characterized by the presence of well-drained, 
sandy soil.  A similar sized area was chosen 300 m from the flux tower at a 
bearing of 61 to represent the wetter eastern border zone of the site.  In 
order to correspond with LAI measurements, conductance samples were stratified 
into two height classes: tall and short.  A tall tree was >1.3 m and a short 
tree was <1.3 m in height.  Samples were also classified as being above or below 
breast height.  During a 30-minute sampling period, samples were collected from 
one or both sites, depending on the time required to establish an equilibrium 
condition in the sample chamber.  For each site, in each sample period, 15 
needle clumps were sampled: 5 clumps from short trees (below breast height), 5 
clumps from tall trees above breast height, and 5 clumps from tall trees below 
breast height.

After several measurement sessions (generally over a few weeks), the tagged 
sample needle clumps were collected.  The needles were removed from each sample 
and counted.  Their projected area was determined by placing them on a light 
table and capturing their area and associated statistics (mean size and shape) 
with an AgVision imaging system (Decagon Devices, Pullman, WA, USA).  The actual 
needle area was found by multiplying the projected area by 2.57, a species-
specific correction factor.  The correction factor was determined as the ratio 
of actual to projected needle area.  Actual leaf area was found by volume 
displacement.

For each sample, the measured conductance represents a relative value that must 
be corrected for the actual needle area of each clump.  This was accomplished by 
multiplying the relative conductance by the ratio of the aperture setting on the 
porometer (i.e., the needle area used by the porometer for its conductance 
measurement) to the actual needle area.  It was assumed that needles which fell 
from the sample during measurements were of average area.  The area of each 
sample was corrected for lost needles by adding the assumed area of lost needles 
(equal to the number of needles lost multiplied by the average needle area) to 
the area of that sample clump for all measurements taken prior to the loss of 
needles.

1996 Experiment

In 1996, the sample area for stomatal conductance was located approximately 30 m 
west of the flux tower and 10 m south of the soil moisture sampling array 
operated by the Hydrology (HYD)-01 group.  The same sampling strategy used in 
1994 was employed: each half-hour when data were collected, 15 trees were 
sampled, with 5 samples taken on needle clumps from tall trees above 1.3 m, 5 
samples from tall trees below 1.3 m and 5 samples were located on small trees, 
each one being <1.3 m. The needle clumps were harvested at the same frequency as 
in 1994, and the same methodology was employed to find the actual leaf area of 
the sample. 

iii) LAI measurements were taken using two plant canopy analyzers (model LAI-
2000, LI-COR, Inc., Lincoln, NE, USA).  One unit, the rover, was positioned 
close to the ground to detect below-canopy readings at chosen sample points 
along the transects.  The other unit was positioned permanently on top of the 
instrument hut, mounted on a tripod at a height approximately 4.75 m from the 
ground, and was operated in remote mode.  This position provided an unobstructed 
view of the sky from well above the mean canopy height (approximately 2 to 3 
meters). Above-canopy readings were recorded automatically every 15 seconds.  
The start and stop times for data collection were programmed by the operator.

Below-canopy measurements were taken near ground level, at a height of 
approximately 0.05 m, and at breast height (1.3 m) every 25 m along the 10 
transects radial to the tower.  To avoid underestimation of LAI from illuminated 
foliage in direct sunlight, measurements were taken just before sunrise and just 
after sunset.  Sky conditions at these times were generally clear.  Both sensors 
were fitted with a lens cap that restricted the field of view to 270.

To ensure that the two LAI-2000 sensors were measuring the same light 
intensities, the units were intercalibrated.  For calibration purposes, the 
sensors were placed side-by-side on the rooftop tripod, leveled, and exposed to 
the same ambient light conditions.  The output of one of the sensors was then 
adjusted to ensure agreement between the light intensities measured by both 
sensors.  In addition, the clocks on both units were synchronized to within <1 s 
of each other.

Each below-canopy measurement was stored as a separate data file.  A single data 
file was created for the above-canopy readings.  The data files from the two 
units were merged using LI-COR software (2000-90 Instrument Support Software v. 
2.15, LI-COR, Inc., Lincoln, NE, USA), which matched each below-canopy reading 
with the above-canopy reading that was recorded at the closest time interval.

Since the LAI-2000 measures only projected leaf area, it was necessary to 
compute a correction factor to obtain the true LAI.  Determination of the 
conifer correction factor (R) followed the methods of Gower and Norman (1991).  
Projected shoot area and total needle area were determined using a computer 
scanning and imaging system (AgVision, Decagon Devices, Pullman, WA, USA).  
Intact shoots were placed on the light table of the AgVision system.  After 
determining the projected area, the shoot was turned 180 and the projected area 
was recalculated.  The shoot projected area (PA(S)) was then determined by 
averaging these two values.  The needles from the shoot were removed and 
measured to determine the total projected needle area (PA).  R was calculated 
from:

R = PA / PA(S)                                               (6.1)

R varied with height on the tree as well as with tree size.  Average values 
found were 2.17, 1.74, and 1.74 for 3-, 2-, and 1-m tall trees.  We also 
examined the shoot clumping factor (SCF) (Chen and Black, 1992; and Smith et 
al., 1993) and found an average value of 1.47 for the site.

A simple conversion factor was derived to convert the projected needle area (PA) 
measured by the AgVision imaging system to the actual needle area (based on the 
assumption that the geometry of jack pine (Pinus banksiana, Lamb.) is best 
represented by a half cylinder.  The relationship is expressed as

AT = PA(1 + pi/2) * 2.57 PA                                   (6.2)

where pi is 3.14, and AT is total needle area (cm2).

The LAI found from destructive sampling of nine trees and expressed as one half 
the needle surface area per unit area was 1.50.  Mean values of apparent LAI for 
all of the sample points on the 10 transects gave an overall site value of 0.79 
( 0.27 s.d.).  Using the sites SCF, the calculated actual LAI (one half-side 
only) is 1.16, which compares reasonably well with the measured LAI of 1.50.

6.2 Field Notes

Special Notes: 1993
All data were averaged over thirty minutes, starting on the hour and half-hour, 
and ending thirty minutes later.  Sampling was continuous, and each day's data 
is from 0600 UTC to 0600 UTC the next day.
LONGWAVE_IN_1138CM was calculated as a residual.
Small nighttime values for SOLAR_RAD_IN_1182CM, SOLAR_RAD_OUT_1158CM,
PPFD_IN_1154CM, and PPFD_OUT_1136CM were set to zero to account for very slight 
zero depressions and elevations in the radiometers.
BIO_TEMP_SMALL_TREES is an average value calculated from the temperatures of the 
small trees at both the north and west sites.
HEAT_STORAGE_TOTAL_AVERAGE is an average value calculated from the total heat 
storage calculated at both the north and west sites.
HEAT_STORAGE_BIO_AVERAGE is an average value calculated from the biomass heat 
storage calculated at both the north and west sites.
Data collection began on DAY 227 at 2330.

Special Notes: 1994
All data were averaged over thirty minutes, starting on the hour and half-hour, 
and ending thirty minutes later.  Sampling was continuous and each day's data is 
from 0600 UTC to 0600 UTC the next day.
LONGWAVE_IN_1138CM was calculated as a residual.
Small nighttime values for SOLAR_RAD_IN_1182CM, SOLAR_RAD_OUT_1158CM, 
PPFD_IN_1154CM, and PPFD_OUT_1136CM were set to zero to account for very slight 
zero depressions and elevations in the radiometers.
BIO_TEMP_SMALL_TREES is an average value found from the temperatures of the 
small trees at both the north and west sites.
R_NET_1170CM_CORRECTED is calculated from day and night time equations taken 
from Hodges and Smith (1997) (see documentation for details).
When SOLAR_RAD_IN_1182CM is greater than zero, CO2_TOTAL_FLUX_900CM is the sum 
of CO2_EDDY_FLUX_900CM and CO2_STORAGE_FLUX_900CM.  If CO2_STORAGE_FLUX_900CM is 
missing, then CO2_EDDY_FLUX_900CM is used for CO2_TOTAL_FLUX_900CM.
When SOLAR_RAD_IN_1182CM is equal to zero, CO2_TOTAL_FLUX_900CM is the sum of 
CO2_FLUX_NIGHT_MODEL_900CM and CO2_STORAGE_FLUX_900CM.  If 
CO2_STORAGE_FLUX_900CM is missing, then CO2_FLUX_NIGHT_MODEL_900CM is used for 
CO2_TOTAL_FLUX_900CM.

Data Period: May 24 - June 6/94 (DOY 144-157)
LONGWAVE_OUT_1138 sensor installed on DOY 148 at 1630
SOIL_TEMP_NORTH_25CM, SOIL_TEMP_NORTH_50CM and SOIL_TEMP_NORTH_75CM 
thermocouples not installed until 179 at 2030.
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
on DOYs 144, 145, 147 from 1830-2230, 148 at 2030 through to 149 at 600 and 149 
from 630-1530 due to weather and 153 from 2100-2130 due to lag tests.
SOLAR_RAD_IN_1182CM, SOLAR_RAD_OUT_1158CM, NET_SOLAR_RAD_1170CM, 
LONGWAVE_IN_1138CM, TOTAL_RAD_IN_1160CM, TOTAL_RAD_OUT_1148CM, R_NET_1170CM, 
R_NET_1170CM_CORRECTED, PPFD_IN_1154CM, PPFD_OUT_1136CM, SURFACE_ALBEDO, 
SOIL_TEMP_NORTH_1CM, SOIL_TEMP_NORTH_5CM, SOIL_TEMP_NORTH_10CM, 
SOIL_TEMP_WEST_25CM, SOIL_TEMP_WEST_50CM, SOIL_TEMP_WEST_75CM, 
SOIL_TEMP_WEST_100CM, DRY_BULB_CANOPY_160CM,DRY_BULB_TEMP_517CM, 
DRY_BULB_TEMP_610CM, DRY_BULB_TEMP_715CM, DRY_BULB_TEMP_770CM, 
DRY_BULB_TEMP_1030CM, WET_BULB_CANOPY_160CM, WET_BULB_TEMP_517CM, 
WET_BULB_TEMP_610CM, WET_BULB_TEMP_715CM, WET_BULB_TEMP_770CM, 
WET_BULB_TEMP_1030CM, BIO_TEMP_SMALL_TREES, BIO_TEMP_MEDIUM_TREES, 
BIO_TEMP_LARGE_TREES, VAPOUR_PRESSURE_CANOPY_160CM, VAPOUR_PRESSURE_517CM, 
VAPOUR_PRESSURE_610CM, VAPOUR_PRESSURE_715CM, VAPOUR_PRESSURE_770CM, 
VAPOUR_PRESSURE_1030CM, WIND_SPEED_517CM, WIND_SPEED_610CM, WIND_SPEED_715CM, 
WIND_SPEED_770CM, WIND_SPEED_1030CM, WIND_DIR_1030CM, WIND_DIR_STDEV_1030CM and 
RAINFALL_250CM values are missing on DOYs 149 from 1530-2300 and 157 from 1500-
1830.
SOIL_HEAT_FLUX_NORTH_10CM, SOIL_HEAT_FLUX_WEST_10CM, HEAT_STORAGE_NORTH_TOTAL, 
HEAT_STORAGE_WEST_TOTAL, HEAT_STORAGE_NORTH_BIO, HEAT_STORAGE_WEST_BIO, 
HEAT_STORAGE_SENSIBLE_AIR, HEAT_STORAGE_LATENT_AIR, HEAT_STORAGE_NORTH_10CM and 
HEAT_STORAGE_WEST_10CM values are missing on DOYs 149 and 157.

Data Period: June 7 - June 20/94 (DOY 158-171)
SOIL_TEMP_NORTH_25CM, SOIL_TEMP_NORTH_50CM and SOIL_TEMP_NORTH_75CM 
thermocouples not installed until 179 at 2030.
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
on DOY 162 from 1800-600, on 163, on 164 from 630-1500 and on 167 at 1900 
through to 168 at 600 due to weather.
SOLAR_RAD_IN_1182CM, SOLAR_RAD_OUT_1158CM, NET_SOLAR_RAD_1170CM, 
LONGWAVE_IN_1138CM, TOTAL_RAD_IN_1160CM, TOTAL_RAD_OUT_1148CM, R_NET_1170CM, 
R_NET_1170CM_CORRECTED, PPFD_IN_1154CM, PPFD_OUT_1136CM, SURFACE_ALBEDO, 
SOIL_TEMP_NORTH_1CM, SOIL_TEMP_NORTH_5CM, SOIL_TEMP_NORTH_10CM, 
SOIL_TEMP_WEST_25CM, SOIL_TEMP_WEST_50CM, SOIL_TEMP_WEST_75CM, 
SOIL_TEMP_WEST_100CM, DRY_BULB_CANOPY_160CM, DRY_BULB_TEMP_517CM, 
DRY_BULB_TEMP_610CM, DRY_BULB_TEMP_715CM, DRY_BULB_TEMP_770CM, 
DRY_BULB_TEMP_1030CM, WET_BULB_CANOPY_160CM, WET_BULB_TEMP_517CM, 
WET_BULB_TEMP_610CM, WET_BULB_TEMP_715CM, WET_BULB_TEMP_770CM, 
WET_BULB_TEMP_1030CM, BIO_TEMP_SMALL_TREES, BIO_TEMP_MEDIUM_TREES, 
BIO_TEMP_LARGE_TREES, VAPOUR_PRESSURE_CANOPY_160CM, VAPOUR_PRESSURE_517CM, 
VAPOUR_PRESSURE_610CM, VAPOUR_PRESSURE_715CM, VAPOUR_PRESSURE_770CM, 
VAPOUR_PRESSURE_1030CM, WIND_SPEED_517CM, WIND_SPEED_610CM, WIND_SPEED_715CM, 
WIND_SPEED_770CM, WIND_SPEED_1030CM, WIND_DIR_1030CM, WIND_DIR_STDEV_1030CM and 
RAINFALL_250CM values are missing on 165 at 1500 through 166 at 600 and on 171 
at 1900 through 172 at 600 due to weather.
SOIL_HEAT_FLUX_NORTH_10CM, SOIL_HEAT_FLUX_WEST_10CM, HEAT_STORAGE_NORTH_TOTAL, 
HEAT_STORAGE_WEST_TOTAL, HEAT_STORAGE_NORTH_BIO, HEAT_STORAGE_WEST_BIO, 
HEAT_STORAGE_SENSIBLE_AIR, HEAT_STORAGE_LATENT_AIR, HEAT_STORAGE_NORTH_10CM and 
HEAT_STORAGE_WEST_10CM values are missing on DOYs 163, 165 and 171.

Data Period: June 21 - July 4/94 (DOY 172-185)
SOIL_TEMP_NORTH_25CM, SOIL_TEMP_NORTH_50CM and SOIL_TEMP_NORTH_75CM 
thermocouples not installed until 179 at 2030.
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
from DOY 184 at 1500 through 189 at 2000 due to generator problems.
WIND_DIR_1030CM sensor malfunction from DOY 172 through to 190 at 2330.  
Reinstalled at 2400 on DOY 190. Consequently, no values of 
WIND_DIR_STDEV_1030CM.
RAINFALL_250CM gauge malfunction on DOY 185 from 30-1900.  Reinstalled at 1930 
on DOY 185.

Data Period: July 5 - July 18/94 (DOY 186-199)
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
from DOY 184 at 1500 through 189 at 2000 due to generator problems.  There are 
no readings on DOYs 191 at 2200 through to 192 at 1730, on 193 at 1600 through 
to 195 at 2100 and on 196 from 1500-1730 due to weather.
SOIL_HEAT_FLUX_NORTH_10CM, SOIL_HEAT_FLUX_WEST_10CM, HEAT_STORAGE_NORTH_TOTAL, 
HEAT_STORAGE_WEST_TOTAL, HEAT_STORAGE_NORTH_BIO, HEAT_STORAGE_WEST_BIO, 
HEAT_STORAGE_SENSIBLE_AIR, HEAT_STORAGE_LATENT_AIR, HEAT_STORAGE_NORTH_10CM and 
HEAT_STORAGE_WEST_10CM values are missing on DOY 190.
WIND_DIR_1030CM sensor malfunction from DOY 172 through to 190 at 2330.  
Reinstalled at 2400 on DOY 190. Consequently, no values of 
WIND_DIR_STDEV_1030CM.

Data Period: July 19 - August 1/94 (DOY 200-213)
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
on DOYs 200 at 1500 through, 201 at 1730 due to instrument malfunction, on DOY 
203 from 1230-1530 due to weather and on DOY 204 from 230-400 due to data 
inconsistencies.  On DOY 206 from 1330-1530 and from 1830-1930 due to data 
inconsistencies and on DOY 207 at 1300 and on DOY 208 from 230-300 due to data 
inconsistencies.

Data Period: August 2 - August 15/94 (DOY 214-227)
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
on DOYs 217 at 2330 through, 218 at 1930, 223 at 2100 through 225 at 1530 due to 
weather.  On DOY 227 at 2400 through 228 at 100 due to data inconsistencies.

Data Period: August 16 - August 29/94 (DOY 228-241)
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
on DOYs 234 at 130 through 235 at 1600, 239 at 1430 through 240 at 1430 due to 
instrument malfunction.  On DOYs 241 at 1730 through 242 at 1430 due to weather.
SOIL_TEMP_WEST_5CM sensor unreliable on DOYs 237 at 2030 through 238 at 230, on 
DOY 238 from 730-1030, on DOY 240 from 630-930, on DOY 241 at 700 through 242 at 
600 due to wet conditions.

Data Period: August 30 - September 12/94 (DOY 242-255)
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
on Jdays 242 from 630-1430, 247 at 1430 through 248 at 1700 due to weather.
LATENT_HEAT_FLUX_900CM and CO2_TOTAL_FLUX_900CM have missing values on Jdays 253 
at 130 through 254 at 600 and on 255 from 630-1500 due to data inconsistency.
SOIL_TEMP_WEST_5CM sensor unreliable on Jdays 242 from 630-1630, on Jday 248 at 
1600 through 249 at 900, on Jday 249 from 1930-2200, on Jday 250 at 2030 through 
251 at 230, on Jday 251 from 600-1100, on Jday 251 at 1800 through 252 at 1500, 
on Jday 252 at 1630 through 253 at 1830, on Jday 255 from 1530-1730, on Jday 255 
at 1930 through 256 at 600 due to wet conditions.

Data Period: September 13 - September 20/94 (DOY 256-263)
LATENT_HEAT_FLUX_900CM, SENSIBLE_HEAT_FLUX_900CM, H2O_FLUX_900CM, 
CO2_TOTAL_FLUX_900CM, CO2_CONC_900CM, SPECIFIC_HUMIDITY_900CM, 
SPECIFIC_HUMIDITY_STDEV_900CM, W_MEAN_900CM and W_STDEV_900CM values are missing 
on DOYs 256 from 1630-1700, and 257 from 1630-1700 due to weather.  On 258 from 
730-1500 and on 259 from 630-1600 due to instrument malfunction.  On DOY 263 at 
1530 through 264 at 600 due to the end of the 1994 field season.
SOLAR_RAD_IN_1182CM, SOLAR_RAD_OUT_1158CM, NET_SOLAR_RAD_1170CM, 
LONGWAVE_IN_1138CM, TOTAL_RAD_IN_1160CM, TOTAL_RAD_OUT_1148CM, R_NET_1170CM, 
R_NET_1170CM_CORRECTED, PPFD_IN_1154CM, PPFD_OUT_1136CM, SURFACE_ALBEDO, 
SOIL_TEMP_NORTH_1CM, SOIL_TEMP_NORTH_5CM, SOIL_TEMP_NORTH_10CM, 
SOIL_TEMP_WEST_25CM, SOIL_TEMP_WEST_50CM, SOIL_TEMP_WEST_75CM, 
SOIL_TEMP_WEST_100CM, DRY_BULB_CANOPY_160CM, DRY_BULB_TEMP_517CM, 
DRY_BULB_TEMP_610CM, DRY_BULB_TEMP_715CM, DRY_BULB_TEMP_770CM, 
DRY_BULB_TEMP_1030CM, WET_BULB_CANOPY_160CM, WET_BULB_TEMP_517CM, 
WET_BULB_TEMP_610CM, WET_BULB_TEMP_715CM, WET_BULB_TEMP_770CM, 
WET_BULB_TEMP_1030CM, BIO_TEMP_SMALL_TREES, BIO_TEMP_MEDIUM_TREES, 
BIO_TEMP_LARGE_TREES, VAPOUR_PRESSURE_CANOPY_160CM, VAPOUR_PRESSURE_517CM, 
VAPOUR_PRESSURE_610CM, VAPOUR_PRESSURE_715CM, VAPOUR_PRESSURE_770CM, 
VAPOUR_PRESSURE_1030CM, WIND_SPEED_517CM, WIND_SPEED_610CM, WIND_SPEED_715CM, 
WIND_SPEED_770CM, WIND_SPEED_1030CM, WIND_DIR_1030CM, WIND_DIR_STDEV_1030CM and 
RAINFALL_250CM values are missing on DOY 263 at 1530 through 264 at 600 due to 
the end of the 1994 field season.
SOIL_HEAT_FLUX_NORTH_10CM, SOIL_HEAT_FLUX_WEST_10CM, HEAT_STORAGE_NORTH_TOTAL, 
HEAT_STORAGE_WEST_TOTAL, HEAT_STORAGE_NORTH_BIO, HEAT_STORAGE_WEST_BIO, 
HEAT_STORAGE_SENSIBLE_AIR, HEAT_STORAGE_LATENT_AIR, HEAT_STORAGE_NORTH_10CM and 
HEAT_STORAGE_WEST_10CM values are missing on DOYs 262 and 263.
SOIL_TEMP_WEST_5CM sensor unreliable on DOYs 256 from 630-1130, on DOY 256 at 
1600 through 257 at 600, on DOY 258 from 500-800, on DOY 258 at 1530 through 259 
at 800, on DOY 259 from 1230-1530, on DOY 259 from 1800-2200 due to wet 
conditions.

Special Notes: 1996
All data were averaged over thirty-minute intervals, starting on the hour or
half-hour, and ending thirty minutes later.  Sampling was continous, and each 
day's data is from 0600 UTC to 0600 UTC the next day. 
LONGWAVE_IN_1138CM was calculated as a residual. 
Small nighttime values for SOLAR_RAD_IN_1182CM, SOLAR_RAD_OUT_1158CM, 
PPFD_IN_1154CM, and PPFD_OUT_1136CM were set to zero to account for very slight 
zero depressions and elevations in the radiometers.
BIO_TEMP_SMALL_TREES is an average value found from the temperatures of the
small trees at both the north and west sites.
R_NET_1170CM_CORRECTED was calculated from day and night time equations 
developed by Hodges and Smith (1997) (see documentation for details).
When SOLAR_RAD_IN_1182CM is greater than zero, CO2_TOTAL_FLUX_900CM is the sum 
of CO2_EDDY_FLUX_900CM AND CO2_STORAGE_FLUX_900CM.  If CO2_STORAGE_FLUX_900CM is 
missing, then CO2_EDDY_FLUX_900CM is used for CO2_TOTAL_FLUX_900CM.
When SOLAR_RAD_IN_1182CM is equal to zero, CO2_TOTAL_FLUX_900CM is the sum of 
CO2_FLUX_NIGHT_MODEL_900CM and CO2_STORAGE_FLUX_900CM.  If 
CO2_STORAGE_FLUX_900CM is missing, then CO2_FLUX_NIGHT_MODEL_900CM is used for 
CO2_TOTAL_FLUX_900CM.

Data Period: May 8\96 - July 3\96 (DOY 129-185)
HEAT_STORAGE_NORTH_10CM and HEAT_STORAGE_WEST_10CM values are missing from DOY 
129 to DOY 178 (inclusive) because soil moisture data were not available.
HEAT_STORAGE_LATENT_AIR is missing DOY 129-133(2030), 137(1400)-141(1700), and 
179(1430-2130).  HEAT_STORAGE_TOTAL_NORTH and HEAT_STORAGE_TOTAL_WEST are 
therefore calculated from the remaining heat storage variables.

Data Period: August 15 - August 28\96 (DOY 228-241)
Values for SOIL_TEMP_NORTH_1CM, SOIL_TEMP_NORTH_5CM, SOIL_TEMP_NORTH_10CM, 
SOIL_TEMP_NORTH_25CM, SOIL_TEMP_NORTH_50CM, SOIL_TEMP_NORTH_75CM, 
SOIL_TEMP_WEST_1CM, SOIL_TEMP_WEST_5CM, SOIL_TEMP_WEST_10CM, 
SOIL_TEMP_WEST_25CM, SOIL_TEMP_WEST_50CM, SOIL_TEMP_WEST_75CM, 
SOIL_TEMP_WEST_100CM, and
RAINFALL_250CM were interpolated on DOY 232 at 1630.

Data Period: October 10 - October 23\96 (DOY 284-297)
WIND_SPEED_517CM, WIND_SPEED_770CM, WIND_SPEED_1030CM, WIND_DIR_1030CM, and 
WIND_DIR_STDEV_1030CM values are missing on DOY 289(2000-0600), 290, 291, and 
292 (0630-1800) because of freezing of the sensors.

Data Period: October 24 - November 6\96 (DOY 298-311)
WIND_SPEED_517CM, WIND_SPEED_770CM, and WIND_SPEED_1030CM values are missing on 
DOY 300(0500-0600), 301, 302, and 303(0630-2030) because of freezing of the 
anemometers.

7. Data Description

7.1 Spatial Characteristics

7.1.1 Spatial Coverage 

All data were collected at the BOREAS NSA-YJP site.  North American Datum of 
1983 (NAD83) coordinates for the site are latitude 55.89575 N, longitude 
98.28706 W, and elevation of 249.29 m.  The prevailing wind direction in the 
area is from the west. Therefore, the access path to the tower and all of the 
hard services (generator, fuel storage area, instrument hut, and storage tent) 
were located east of the tower.

Porometric data were collected at two locations on the YJP site in 1994. One 
location was designated as dry because it was located on the dry, sandy soil 
near the flux tower, and the other location was designated as wet because it 
was located on the wetter part of the site east of the flux tower.  The wet site 
was 290 m from the tower at a bearing of 61 degrees, and the dry site was 150 m 
from the tower at a bearing of 56 degrees.  The strategy of choosing two sample 
positions was to see whether the clearly different soil moisture status of the 
sites influenced the behavior of stomatal conductance.  In 1996, one porometric 
sample zone was located approximately 40 m from the tower at a bearing of 250 
degrees.  This site was chosen in order to be close to the dense array of 
continuous soil moisture sample profiles run by HYD-01.

7.1.2 Spatial Coverage Map

Not applicable.

7.1.3 Spatial Resolution 

The data collected from towers are usually thought of as point data. However, 
they actually represent an integrated response to the surface/atmosphere 
interaction, especially in terms of the eddy flux data, which are considered to 
represent an integrated upwind surface source region (Leclerc and Thurtell, 
1990; Schmid and Oke, 1990). In general, at the YJP the fluxes apply to the 
surface between 20 to 400 meters upwind. At the fen, where fetch in certain wind 
directions is limited, data uncertainties may occur (see Section 10.1).

7.1.4 Projection

Not applicable.

7.1.5 Grid Description

Not applicable.

7.2 Temporal Characteristics

7.2.1 Temporal Coverage

The start and stop times for the experiments were as follows:

15-AUG-1993 to 31-AUG-1993
25-MAY-1994 to 19-SEP-1994
30-APR-1996 to 15-NOV-1996

7.2.2 Temporal Coverage Map

Not applicable.

7.2.3 Temporal Resolution

With one exception, the data values submitted to BORIS were integrations of the 
conditions for the 30-minute reporting periods.  The exception is the porometric 
data, and specifically the stomatal conductance of the jack pine, which is 
submitted as shorter-term averages.

Meteorological data were output at 15- and 30-minute intervals depending upon 
the variable. The 15-minute data included only absolute wet- and dry-bulb air 
temperatures and soil temperatures, which were used for heat storage 
calculations (described below).  All signals, except temperature differences, 
were averaged over 30-minute periods.  Only the 30-minute data were reported to 
BORIS.  Eddy covariance data were output every 30 minutes.

Porometry data and other biophysical measurements were conducted at irregular 
sampling intervals as conditions and resources permitted.  Dates and times are 
noted in the data submissions.

7.3 Data Characteristics

Data characteristics are defined in the companion data definition file 
(tf10flux.def).

7.4 Sample Data Record

Sample data format shown in the companion data definition file (tf10flux.def).

8. Data Organization

8.1 Data Granularity

All of the NSA-YJP Tower Flux, Meteorological, and Porometry Data are contained 
in one data set.

8.2 Data Format

The data file contains numerical and character fields of varying length 
separated by commas. The character fields are enclosed with single apostrophe 
marks. There are no spaces between the fields. Sample data records are shown in 
the companion data definition file (tf10flux.def).

9. Data Manipulations

9.1 Formulae

i) Net Solar Radiation (W/m2)

Net solar radiation (K*) is the difference between incoming solar radiation
(Kd) and reflected solar radiation (Ku):

K* = Kd  Ku                                                  (9.1)

ii) Incoming Longwave Radiation (W/m2)

Incoming longwave radiation (Ld) is calculated as a residual from the net 
radiation balance, where net radiation (Q*) is the sum of net solar radiation 
(K*, see e.g. 9.1) and net longwave radiation (L*).  L* is the difference 
between incoming longwave radiation (Ld) and outgoing longwave radiation (Lu).

Q* = Kd - Ku + Ld  Lu                                        (9.2)

iii) Total Incoming Radiation (W/m2)

Total incoming radiation (Qd) is the sum of all incoming radiation:

Qd = Kd + Ld                                                  (9.3)

iv) Total Outgoing Radiation (W/m2)

Total outgoing radiation (Qu) is the sum of all outgoing radiation:

Qu = Ku + Lu                                                  (9.4)

v) Net Radiation corrected (W/m2)

Measured net radiation (Q*) was corrected using a set of site-specific day- and 
night-time equations developed by Hodges and Smith (1997).  These equations 
(shown below) were used for all years of data, excluding data collected in 1993 
at both fen and YJP.  The use of the day or night equation is based on measured 
incoming solar radiation.  When Kd>5.00 W/m2, daytime equations are used.  The 
relevant equations for the fen and YJP are:

Site        Time of day       Correction equation
Fen            DAY            Q*corr = 0.957(Q*) + 3.2        (9.5)
               NIGHT          Q*corr = 1.079(Q*) + 11.1       (9.6)
YJP            DAY            Q*corr = 0.992(Q*) + 7.6        (9.7)
               NIGHT          Q*corr = 1.178(Q*) + 11.6       (9.8)

vi) Surface Albedo (dimensionless)

Surface albedo (a) is the ratio of the amount of radiation reflected by a body 
to the amount incident upon it:

a = Ku/Kd                                                     (9.9)

vii)  Total CO2 Flux (umol/(m2 s1))

The total CO2 flux (FCO2) is the sum of the eddy flux (FeCO2) and the storage 
flux (FsCO2):

FCO2 = FeCO2 + FsCO2                                          (9.10)

In 1994 and 1996 at the YJP site, a night model (CO2night) was used in the 
calculation of the total CO2 flux (when Kd=0), and 

CO2night = -2.4883 + 0.82337(Ts10avg) - 0.6777(Ts75avg),      (9.11)

where Ts10avg and Ts75avg are the average soil temperatures from the north and 
west zones from a depth of 10 and 75 cm, respectively. Then,

FCO2 = CO2night + FsCO2                                       (9.12)

viii) Heat Storage (W/m2)

Total heat storage (G_total) is based on the sum of heat storage from several 
environmental compartments:

G_total = G + Ga + Ge + Gveg                                 (9.13)

where G = soil heat flux
     Ga = sensible heat storage in the air
     Ge = latent heat storage in the air
   Gveg = heat storage in the vegetation

Only G is measured, and the remaining variables are calculated using the 
formulae given by Thom (1975):

Ga(T) = 0.33 zr dTa(t)                                        (9.14)
Ge(T) = 0.5 zr de(t)                                          (9.15)
and
Gveg(T) = 0.8 Mv dTb(t)                                       (9.16)

where zr is the reference height (in this case the height of the net 
pyrradiometer)(m); dTa, de, and dTb are the rates of change in air temperature 
(C/s), vapor pressure (kPa/s), and biomass temperature (C/s), respectively, 
for time step t; and Mv is the standing green mass of vegetation over unit area 
(kg/m2).  Theoretically, Ga and Ge are integrated over the height interval 
between the surface and zr.  In this study, the calculations were performed for 
discrete layers represented by the profile psychrometer heights and summed to 
get the totals.  The calculation of all minor heat storage terms in the energy 
balance were calculated with the Fortran program called STORAG.  An explanation 
of this program is given in Section 9.1.1, and a description of the command 
files used to process the data is given in Section 9.2.1.

Ground heat flux at the YJP site is computed in the usual sense, where the heat 
flux plate reading is summed with heat storage from the soil layer between the 
plate and soil surface.

The operational equations are:

G = G(z) + S                                                  (9.17)
S = CdTs(t) z/1800                                            (9.18)
and
C= Cm Xm + Cw Xw + Co Xo                                      (9.19)

where G is the ground heat flux at the soil surface integrated over a 30-minute 
time interval (W/m2), G(z) is the soil heat flux measured at depth z (W/m2), and 
S is the flux equivalent to the heat stored between the surface and the heat 
flux plates during the time interval (t=1800s) (W/m2).  C is the volumetric heat 
capacity of the soil (J/(m3 C)), dTs(t) is the temperature change in the soil 
layer above the heat flux plate over the time interval (C/s), and z is the 
depth of the heat flux plates (m).  The volumetric heat capacity is obtained 
from measurements of the volume fractions (X) of the mineral, water, and organic 
soil components (subscript m, w, and o, respectively) and their respective heat 
capacities (Cm, Cw, and Co).

Heat storage calculated for the YJP site was distinguished by zone in 1994 and 
1996.  Separate soil heat fluxes were measured for the north and west zones 
(G(z)n and G(z)w, respectively).  Calculated variables include sensible heat 
storage in the air (Ga), latent heat storage in the air (Ge), and heat storage 
in the vegetation at both the north and west sites (Gvegn and Gvegw, 
respectively).  Heat storage in the soil volume above 10 cm depth (G10) is also 
a part of G_total in 1994 and 1996, resulting in the following equations:

G_totaln = G(z)n + Ga + Ge + Gvegn + G10                      (9.20)
G_totalw = G(z)w + Ga + Ge + Gvegw + G10                      (9.21)

In 1993, an average value of the north and west zones is presented for G_total
and Gveg.

Ground heat flux at the fen in 1994 only (Gfen) was computed by adjusting the 
heat flux plate readings from the hollow (Ghol) with a correction factor 
determined from calorimetric methods.  In the following explanation, Gpla is 
equal to Ghol. Hence,

G = G(z)CF                                                    (9.22)
where
CF = Gcal/Gpla                                                (9.23)

in which CF is a correction factor (3.04) determined from calorimetric 
calculations of heat storage in the soil profile (Gcal) and the time-integrated 
flux measured by the heat flux plates (Gpla).  Gpla is calculated by summing the 
30-minute average heat flux plate readings multiplied by 1800 seconds over a 
specified time interval (usually 10-14 days).  Gcal is the total heat storage in 
the soil profile calculated from individual soil layers represented by the 
measured temperature profile(s), plus the heat flux out the bottom of the soil 
profile (GB).

Heat storage in the individual layers, S(i) is computed as: 

S(i) = CdT(t)z                                                (9.24)

where symbols are defined as above.  C varies between 3.48 x 106 J/(m3 C) for 
saturated peat soil and 0.58 x 106 J/(m3 C) for dry peat soil. The flux out the 
base of the soil profile is calculated as:

GB = -Ks dT/dz                                                (9.25)

where -Ks is the thermal conductivity of saturated peat soil (0.5 W/(m C)) and 
dT/dz is the temperature gradient at the base of the soil profile.

In 1993, 1995, and 1996, no correction factor was applied to the fens soil heat 
flux data (see Section 10.2.2). In these years, the soil heat flux from the 
hollow (Ghol) was used in the calculations of G_total.

ix) Stem Temperatures (C)

Stem temperatures were recorded at YJP in 1993, 1994, and 1996 from both the 
north and west sites at YJP.  Stem temperatures from small (Tbsw), medium 
(Tbmw), and large trees (Tblw) were recorded at the west site, whereas only 
small trees were sampled at the north site (Tbsn).  Stem temperatures recorded 
in the data files were taken from the west site, with the exception of stem 
temperatures from small trees.  Tbs is an average of the stem temperatures from 
both the north and west sites:

Tbs = (Tbsn + Tbsw)/2                                         (9.26)

x) Specific Humidity (g/kg)

Specific humidity (SH) and the standard deviation of specific humidity (sSH)
were calculated using measured air temperature (T_air), vapor density (q), and 
the standard deviation of ln q (sln q).

Air density (rho) is found as a function of T_air, where

if     T_air>30  then rho = 1.149 - 0.0036 (T_air - 30.01)   (9.27)
if  25<T_air<30  then rho = 1.168 - 0.0038 (T_air - 25.01)   (9.28)
if  20<T_air<25  then rho = 1.188 - 0.0040 (T_air - 20.01)   (9.29)
if  15<T_air<20  then rho = 1.209 - 0.0042 (T_air - 15.01)   (9.30)
if  10<T_air<15  then rho = 1.230 - 0.0042 (T_air - 10.01)   (9.31)
if   5<T_air<10  then rho = 1.252 - 0.0044 (T_air -  5.01)   (9.32)
if   0<T_air<5   then rho = 1.275 - 0.0046 (T_air -  0.01)   (9.33)
if  -5<T_air<0   then rho = 1.229 - 0.0048 (T_air +  4.99)   (9.34)
if -10<T_air<-5  then rho = 1.324 - 0.0050 (T_air +  9.99)   (9.35)
if -15<T_air<-10 then rho = 1.350 - 0.0050 (T_air + 14.99)   (9.36)
if -20<T_air<-15 then rho = 1.376 - 0.0054 (T_air + 19.99)   (9.37)

The specific humidity is found from the vapor density (g/m3), measured by the 
krypton hygrometer at each site, and

q = (ln s - ln v)/kx                                          (9.38)

where s = the signal voltage from the hygrometer (mv), v is the intercept of the 
hygrometers calibration (4054 mv for the fen and 4528 mv for the YJP), k is 
absorption coefficient for water vapor (-0.141 m3/(g cm) for the fen and -0.133 
m3/(g cm) for the YJP), and x is the path length of the hygrometer (1.542 cm for 
the fen and 1.400 cm for the YJP).  Then,

SH = q/rho,                                                   (9.39)
and
sSH = (e^|sln q|)/rho                                         (9.40)

where s indicates the standard deviation.

xi) Convective Heat Fluxes (H and LE)

The sensible heat flux was found from equation 3.2 which states that

H = rho Cp <w'T'>                                             (9.41)

where the variables have their usual meanings.  Webb (1982) showed that the air 
density and specific heat of air are functions of both the airs temperature and 
vapor pressure, and that air temperature had the largest control.  Thus, in our 
calculations, the rho Cp term was corrected for changing temperature and air 
pressure as follows:

rho Cp = Cp(d) (P M/R T),  (9.42)

where Cp(d) is the specific heat of dry air, P is the atmospheric pressure, M is 
the molecular weight of dry air, R is the universal gas constant, and T is the 
air temperature.  In the 1994 experiments, P was obtained from Thompson airport 
and read into the data logger once a day, usually about 1500 UTC, when the site 
was first visited.  In 1996, analog pressure sensors at the YJP and fen were 
recorded P every half-hour.  The air temperature that was used was the average 
value from the previous half-hour, which was updated on a continuous basis 
automatically by the data logger.  The precision of this correction was improved 
in 1996 because we incorporated air pressure sensors into the measurement 
packages at each site, and this allowed the use of the previous half-hours air 
pressure as well as temperature in equation 9.41.

The value of L, the latent heat of vaporization, in the eddy covariance 
measurement of latent heat flux (equation 3.1) was found as a function of air 
temperature from the equation

L = 2501 + (-2.363) T + (-0.00023) T2,                       (9.43)

where T is the air temperature averaged over the previous half-hour.  Equation 
9.42 was part of the online calculations.

The krypton lamp in the hygrometer has two emission lines, a major line at 
123.58 nm, and a minor line at 116.49 nm.  Both lines are absorbed by both water 
vapor and oxygen.  It is necessary to account for the effect of absorption by 
oxygen on the value of vapor density in order to correct the latent heat flux.  
The oxygen correction is a function of atmospheric pressure and temperature, and 
Tanner, et al. (1993) provide the appropriate equations to find the oxygen 
correction.  At standard atmospheric pressure (101.3 kP) and temperature (305 
K), the pressure correction is small in comparison to that caused by 
temperature, and it is usual to correct for oxygen absorption based only on 
temperature.  This procedure was followed in this experiment.

Webb et al. (1980) described the influence of sensible heat and vapor fluxes 
that cause changes in the density of atmospheric constituents, and the necessary 
corrections to the flux associated with these fluctuations.  These corrections 
are usually termed the Webb, Pearman, and Leuning (WPL) corrections, and they 
were applied to the latent heat flux in this experiment (Joiner, 1994).  The WPL 
correction due to the sensible heat flux is approximately five times larger than 
that due to the vapor flux itself (Tanner et al., 1993). 

xii) Carbon Dioxide Flux

Because we used a closed-path IRGA and the air sample was delivered to the 
instrument through a sample tube, there is a time delay, or lag, in the 
concentration of CO2, measured in the IRGA, and the measured vertical wind in 
the free atmosphere around the sonic.  If the CO2 concentration data were not 
corrected for lag, we would not calculate the correct covariance, and the flux 
of CO2 would be incorrect.  We found the lag for our CO2 systems at fen and YJP 
empirically.  While continuously monitoring the output of CO2 and vertical wind, 
we introduced a bubble of nitrogen in the vicinity of the sample tube intake.  
The arrival of the nitrogen in the sample cell of the IRGA caused a discernable 
spike in the CO2 time series.  We identified formally the time of occurrence of 
the spike by lag correlation analysis of CO2 concentration and vertical wind.  
The lag was where the correlation coefficient between CO2 and vertical wind was 
a maximum.  Site-specific lag times were programmed into the data loggers at 
each site, and these lags allowed us to compute a covariance using the correct 
values of CO2 and vertical wind.

The concentration of CO2 measured by an IRGA is dependent on pressure.  Changing 
pressure changes the calibration of the instrument (span/voltage difference) by 
changing the span.  The span is the difference in concentration between the high 
and low span gases; in our case approximately 30 to 40 ppmv. The effect of 
changing pressure on the IRGAs calibration was corrected online. 

Changes in the airs temperature and water vapor density, which in turn are 
related to the sensible and latent heat fluxes, affect the concentration of CO2 
and hence the flux of CO2 (Webb et al., 1980).  In postprocessing, the CO2 flux 
was corrected for changing density and vapor flux (Joiner, 1994).  The 
correction includes a correction for the cross-sensitivity of the IRGA to water 
vapor and carbon dioxide (Leuning and Moncrieff, 1990; Leuning and King, 1992).

9.1.1  Derivation Techniques and Algorithms

STORAG is the general name for a Fortran program that calculates the minor heat 
storage terms in the energy balance.  There are several operational versions of 
the program that differ depending upon the available data (see Section 9.2.1).  
Also, ENBAL, a Fortran program to solve for the terms of the radiation balance, 
was used in the analysis.  Both STORAG and ENBAL work on the principle of GET 
commands that read input data into memory from various files, and when 
sufficient variables are read to solve the control equations, the calculations 
get done and are stored in output tables that can be delivered to spreadsheets 
or plotting packages for further processing and plotting.  There is a worked 
example of the operation of STORAG in Section 9.2.1 that illustrates not only 
the specific features of STORAG but also the general nature of both programs. 

9.2  Data Processing Sequence

9.2.1  Processing Steps

Two versions of STORAG were used in the calculations of heat storage depending 
on what data were available: STORY94.exe and STORY96.exe.  STORY94.exe, used on 
1993, 1994, and 1995 data, calculated heat storage variables from wet-bulb and 
dry-bulb temperatures, net radiation, soil heat flux, and soil temperatures.  
STORY96.exe was used on the 1996 data where relative humidity (RH) was an input 
measured variable, which replaced its calculation using wet-bulb temperatures.

A command file is used to run the STORAG program.  It comprises a list of GET 
statements that will select variables from a specified column in a specified 
file.  The last two numbers in the GET statement are the slope and intercept of 
the equation to be used with that data.  This is useful if the input data are in 
the wrong units and a linear calibration can be applied.  Other variables are 
set using SET statements.  Variables used in the STORY94 program are:

Q*       Net radiation
QGZ      Soil heat flux
TS1-3    Soil temperatures from depths of 1, 5, and 10 cm, respectively
TB       Biomass temperature (see Section 9.2.2)
TD1-6    Dry-bulb temperatures
Tw1-6    Wet-bulb temperatures (in STORY96 RH is used instead)
XW       Soil moisture content
HCS      Heat capacity of soil
TOL      Thickness of the organic layer
DS       Depth of temperature measurements
ZR       Height of the net radiation measurement
ZCQ      Height of canopy, height of net pyrradiometer
MV       Green mass of vegetation
CON      Constant used in equations determining Ga, Ge, and Gveg

An example of the command file used to run STORAG is listed in Table 16 for one 
day. All commands must be in capital letters, Q* and QGZ data must be 30-minute 
averages, and the remaining temperatures are 15-minute averages.

Table 16. Example command file for STORAG, a program to find the minor heat 
storage terms in the surface energy balance.

SETPAUSE OFF
CLEAR
TITLE  YJP NORTH FOREST SITE  ENERGY STORAGE  MAY-24-1994 (144)
SETTIME 0.25 0.25 95
GET(Q*)  Y94307E.144 (24X,F8.0)  1.0 0.0
GET(QGZ) Y94307E.144 (112X,F8.0) 1.0 0.0
GET(TS1) Y94157E.144 (200X,F8.0) 1.0 0.0
GET(TS2) Y94157E.144 (208X,F8.0) 1.0 0.0
GET(TS3) Y94157E.144 (216X,F8.0) 1.0 0.0
GET(TB)  Y94157E.144 (40X,F8.0)  1.0 0.0
GET(TD1) Y94157E.144 (48X,F8.0)  1.0 0.0
GET(TD2) Y94157E.144 (56X,F8.0)  1.0 0.0
GET(TD3) Y94157E.144 (64X,F8.0)  1.0 0.0
GET(TD4) Y94157E.144 (72X,F8.0)  1.0 0.0
GET(TD5) Y94157E.144 (80X,F8.0)  1.0 0.0
GET(TD6) Y94157E.144 (88X,F8.0)  1.0 0.0
GET(TW1) Y94157E.144 (96X,F8.0)  1.0 0.0
GET(TW2) Y94157E.144 (104X,F8.0) 1.0 0.0
GET(TW3) Y94157E.144 (104X,F8.0) 1.0 0.0
GET(TW4) Y94157E.144 (120X,F8.0) 1.0 0.0
GET(TW5) Y94157E.144 (128X,F8.0) 1.0 0.0
GET(TW6) Y94157E.144 (136X,F8.0) 1.0 0.0
SET(XW)  0.08 0.08
SET(HCS) 0.1455 0.2067
SET(TOL) 0.03
SET(DS)  0.01 0.05 0.1
SET(ZR)  1.5 5.07 6.0 7.05 7.6 10.2
SET(ZCQ) 3.0 11.60
SET(MV)  0.888
SET(CON) 0.8
SHOW
WRITE    Y94STORN.144
WRITESTO Y94QSN.144

9.2.2  Processing Changes

Where one level of air temperature was missing from a file used in STORAG, the 
GET statement was changed to read the value from the nearest level.  For 
example, if the third level of temperature is missing, the value from the fourth 
level could be used instead.

Mass of vegetation (MV) is zero in the fen calculations. For heat storage 
calculations at YJP in the west site, MV = 2.22. Because there were only small 
trees in the north site, MV = 0.888 for that site.  Biomass temperature (TB) is 
zero in the fen calculations, whereas it is based on the stem temperatures at 
YJP.  In the north site, TB = Tbsn.  In the west site, the following weighted 
average, based on the percentage occurrence of small, medium, and large trees, 
was used to determine TB:

TB = 0.4 Tbsw + 0.486 Tbmw + 0.114 Tblw                       (9.44)

The STORAG program does not accept zero in the command file; therefore, the TB 
multiplier, the thickness of the organic layer (TOL), the height of the canopy, 
and the mass of vegetation (MV) were set to 0.000001 in the fen calculations, 
creating insignificant values in the calculated heat storage.    

9.3  Calculations

9.3.1  Special Corrections/Adjustments

The following rules were followed in preparing the data files:

i) Any small negative values of Kd and Ku (<1 W/m2) were changed to zero and Ld, 
Qd, Qu, and the  albedo were recalculated accordingly; negative values occur as 
a result of zero depression on the instruments.

ii) All negative values of incoming and reflected photosynthetic photon flux 
density (PPFDd and PPFDu) were changed to zero; as is the case with 
pyranometers, small negative values result from zero depression.

iii) When FsCO2 was missing and Kd>0, then  FCO2 = FeCO2.

iv) When FsCO2 was missing and Kd=0, then  FCO2 = CO2night.

v) Latent heat flux (LE) was flagged (i.e., changed to -999) when LE<-50 W/m2.

vi) Sensible heat flux (H) was flagged when H<-70 W/m2.

vii) All negative wind speeds were flagged.

viii) Where LE was flagged and vertical wind speed (w) was >2 or <-2 m/s, w was  
flagged.

ix) Where between one and three half-hourly average values of a variable were 
missing, a linear interpolation was done, assuming that the meteorological 
conditions were steady and a clear temporal trend was present before and after 
the data gap.

9.3.2  Calculated Variables

Formulae for the following list of calculated variables can be found in
Section 9.1: K*, Ld, Qd, Qu, Q*, Q*corr, a, FCO2, CO2night, G_total, Ga, Ge, 
Gveg, G10, SH, and sSH.

9.4  Graphs and Plots

Day 260 in 1996 was chosen because it was a clear day and it shows many 
interesting contrasting features of the radiation, energy, and CO2 balances of 
the two sites (Figure 4).  The time shown in the figure is UTC.  The most 
notable differences in the radiation balances between the two sites (Figure 4A 
and 4B) occur in the net radiation (Q*) and reflected solar radiation (Ku) 
components: the latter is larger and the former is smaller at the fen as a 
result of i) the larger albedo at the fen and ii) the higher surface 
temperatures on the jack pine; which increase the outgoing longwave radiation 
(Lu) from the drier surface; the greatest contrast in Lu occurs early in the 
day.  The incoming solar radiation (Kd) and incoming longwave radiation (Ld) do 
not indicate substantial differences between the sites.

The fen had started to senesce by day 260; as a result, the majority of the 
available energy goes into sensible heat flux (average Bowen ratio 2.0) (Figure 
4C).  The YJP was still actively transpiring (average Bowen ratio 1.0), except 
for a short period in the middle of the day when the sensible heat flux exceeds 
the latent heat flux (Figure 4D).  The value of the total heat storage (G_total) 
includes the soil heat storage and biomass storage from the north site. 

The impact of senescence is very noticeable in the different net CO2 flux 
patterns.  The fen is either effluxing or in a state of zero net exchange for 
the majority of the day (Figure 4E), but there is some very weak uptake in the 
late morning.  The jack pine shows vigorous uptake for the whole daylight period 
and consistent efflux in the nighttime period at the start of the day (Figure 
4F).  The pattern of efflux breaks down late in the day under the very calm wind 
speed conditions (Figure 4H).

The pattern of wind at the fen is characterized by either very low wind speed or 
complete calm during the night and maximum values of 5 m/s during the daylight 
period (Figure 4G).  The increase of wind speed in the morning and the decrease 
in the evening are very sharp.  The pattern at the YJP is quite different early 
in the day, when the wind speed increases gradually to a maximum of only 3 m/s 
by the evening.  The precipitous drop in wind speed at 0000 UTC is the same 
pattern as at the fen.  The direction of the wind was steadier at the fen, where 
it blew from the southeast from 1200 UTC onwards.  At the YJP, the direction was 
more easterly for the majority of the day.  It is clear that the fen has its own 
particular wind climate, and on very calm nights such as the start of day 260, 
it is much calmer than the more open YJP site (compare Figures 4G and 4H).

The slightly higher and more gradually declining air temperatures at the YJP in 
the early part of the day (Figure 4H) are consistent with the presence of the 
higher wind speeds, which would have mixed the lower atmosphere more 
effectively.  The increased mixing would hinder the development of a surface 
temperature inversion and raise the air temperature. It is important to note 
that the eddy covariance measurement of CO2 was very successful at this time of 
the day, when a constant efflux of 1 micromole/ (m2 s1) was measured (Figure 
4F). The same is not true for the fen, where the CO2 series is quite jagged 
(Figure 4E) as a result of measured negative fluxes that have been set to zero 
as part of the data management. Clearly, the measurement of the flux was 
breaking down at the fen under the totally calm wind speed conditions (Figure 
4G).

INSERT FIGURE 4 HERE (FILE IS Figure4.JPG)

10. Errors

10.1 Sources of Error

There are a number of sources of error in the data.  In general, these sources 
can be identified as: i) instrument error, i.e., the error component from the 
transducer itself, ii) a component from the measurement device, and iii) a 
component dependent upon field placement.  Not all of the components of error 
are easily evaluated, and the most difficult to evaluate through a formal 
analysis is that due to field placement.  We believe that we minimized field 
placement error, but we do not have a formal way of verifying this claim.  We do 
claim that all instruments were located according to normal field practice, and 
a close watch was kept by field staff for any apparent aberrant output from the 
instruments.

10.2 Quality Assessment

All aberrant data occurrences found in the field were noted in the field log and 
examined in detail during postprocessing.  There are a number of reasons for the 
occurrence of aberrant values.  In our particular case, the two most common 
reasons were i) shutdown of the CO2 system for calibration, which was done once 
a day and which resulted in the loss of one 30-minute average value, and ii) 
covering of the sonic anemometer to prevent its damage by heavy rain.  There 
were various other occurrences of apparently aberrant values unrelated to these 
two causes.  In order to try to identify aberrant behavior more formally, during 
postprocessing all raw time series were scanned for each day and the outliers 
from the series were identified and examined in detail. In addition, the 
calculated time series of fluxes were examined for outliers.  Typically, when an 
outlier was found, the field notes were consulted to see if some action on the 
tower or in the vicinity of the instrument had been recorded that would have 
caused the outlier to occur.  Irrespective of whether we could tie the outlier 
to a cause, a simple linear interpolation was applied if the outlier was judged 
aberrant, the period of bad data was short, and steady-state conditions applied.  
If it was clear that the data point was wrong and it could not be corrected or 
interpolated, it was flagged and a missing value place holder inserted.  It is 
admitted that this process is not totally objective and it does involve some 
judgments based upon field experience.  We do claim that the data acceptance 
criteria were conservative; i.e., it was normal to reject an apparently aberrant 
data point unless there was very strong evidence to the contrary.

10.2.1 Data Validation by Source

The overall best estimates of accuracy of the primary variables are as follows:

net radiation:      +/- 5%
PPFD:               +/- 7%
solar radiation:    +/- 1%
soil heat flux:     +/- 5% for YJP; no estimate is made for fen
latent heat flux:   +/- 15 to 20%
sensible heat flux: +/- 15 to 20%
CO2 flux          : +/- 20% or +/- 0.2 umol/(m2 s2), whichever is larger
wind speed (model 12102): +/- 0.3 m/s from 0 to 30 m/s
wind direction (model 12302): +/- 3.0 degrees
air temperature(T/RH sensor, model 41372): +/- 0.3 C from -50 to + 50 C
relative humidity (T/RH sensor, model 41372): +/- 3% between 10 and 90% RH, and
                      +/- 5% between 0 and 10% and between 90 and 100% RH
rainfall (model TE525M, Texas Instruments): +/- 1% up to 10 mm/h
                                            +/- 3% between 10 and 20 mm/h
                                            +/- 5% between 20 and 30 mm/h
 
In 1993, 1994, and 1996, no correction factor was applied to the fens soil heat 
flux data.  Rather, we report the flux values measured by the plate(s).  This is 
a puzzling result, but if the same correction value had been applied as in 1994, 
totally unreasonable values of flux would have resulted.  In fact, the energy 
balance closures would have consistently been much greater than unity as a 
result.  This points out the difficulty of measuring heat storage in the peat 
soil.  We suggest that our application of different methodologies can be 
explained in the following way.  In 1994, only the plate in the hollow exhibited 
any diurnal pattern, but the size and amplitude of the measured flux was tiny. 
The signal from the plate in the hummock showed zero amplitude, and was a flat 
line during the whole day, we believe as a result of poor thermal contact 
between the plate and the peat.  Such patterns were not observed in the other 
sample years, when both plates exhibited similar and significant signal sizes 
and diurnal amplitudes.  Furthermore, accepting the measured fluxes in these 
sample years results in reasonable energy balance closures.  However, the 
measurement of soil heat flux on a fen remains a confounding problem, and it 
requires further careful assessment in terms of measurement methodology.

Another problem that caused serious questioning of our methodology was the 
measurement of the CO2 flux at night.  This problem was most apparent at the 
YJP.  After examination of the data, it was concluded that the measured fluxes 
should be replaced with modeled values in order to obtain reasonable diurnal 
patterns.  The issue of how best to measure CO2 fluxes at night under low 
turbulent mixing conditions remains a priority. In addition, there are 
outstanding issues on the best way to model the nighttime CO2 flux.

2	Confidence Level/Accuracy Judgment

None given.

10.2.3 Measurement Error for Parameters

See Section 10.2.1.

10.2.4 Additional Quality Assessments

None given.

10.2.5 Data Verification by Data Centre

Data were examined to check for spikes, values that were four standard 
deviations from the mean, long periods of constant values, and missing data.

11. Notes

11.1 Limitations of the Data

At this time (June 1998), the data series are not continuous.  Where there were 
measurement problems, e.g., as a result of a sensor failure or a power failure, 
missing value placeholders have been inserted.  We are working toward providing 
robust methods for reconstruction of large data gaps.  One method that has been 
fairly successful is to construct the diurnal patterns of fluxes using ensemble 
averaging.  However, for users who require unbroken time series of 30-minute 
averages, these data will fall short.  In most instances of a small gap, say one 
or two contiguous half-hours, in a period of steady-state atmospheric 
conditions, straight linear interpolation should work satisfactorily.  If the 
atmospheric conditions are changing rapidly, or if the gap is large, say half a 
day, then a rigorous interpolation method will be required.  Please consult the 
PI for progress on the development of interpolation routines for large data 
gaps.

At this time (June 1998), the eddy covariance flux data (sensible and latent 
heat and CO2) at the YJP site are from the Campbell Scientific single-axis sonic 
anemometer.  A second sonic anemometer (Applied Technologies, Inc., 
(ATI), Boulder, CO, USA) was operational at the site in 1996, and both were 
located at the same height and orientation on the flux tower.  The final 
calculation of the fluxes based on the ATI sonic data are not yet complete and 
are not included in this data set.

11.2 Known Problems with the Data

Where tower flux sites do not have adequate upwind fetch, uncertainties are 
introduced into the interpretation of the flux data.  We believe this may have 
been a problem at the fen.  The eddy covariance instruments were located at a 
height of 4.5 m above the surface.  Using the standard micrometeorological 
"rule-of-thumb" for fetch-to-height ratio of 100:1, a 450-m fetch is required in 
all directions around the fen tower.  The site did not meet this criterion.  
Fetch was limited along the northeast shore in the azimuth directions (from 
magnetic north) 350-0-125 degrees.  Minimum fetch in this quadrant was 
approximately 150 m at a bearing 65 degrees.  Similarly, fetch was limited along 
the south shore in the bearing 160-235 degrees.  Minimum fetch in this quadrant 
was 220 m at the bearing 205 degrees.  Fetch in all other directions exceeded 
450 m.  Measurements for all wind directions were reported in the data set, and 
users are cautioned as to this possible source of uncertainty.

Fetch to height ratios at YJP were greater than 100:1 in all directions.  
However, the sector azimuth 45-140 degrees contains the access trail to the 
tower, the instrument and data processing hut, and the generator hut.  Some 
contamination of fluxes measured from this direction may have occurred.

11.3 Usage Guidance

In 1994 at YJP, recording of the deep soil temperatures (0.25, 0.50, and 0.75 m) 
at the north soil heat flux site did not start until DOY 179 1994.  This 
contrasts to the measurements at the west site, where recording began on DOY 
144.  As a result, lower minimum deep soil temperature values were observed at 
the west site.  This phenomenon is reflected in the max/min summary in Section 
7.3.5..

In the modeled nighttime carbon dioxide flux series, all negative values 
(uptake) were kept in the data set because there was no rationale for removing 
them.  They occurred as a result of the nature of the empirical model (equation 
9.11) used for the estimate.

11.4 Other Relevant Information

None.

12. Application of the Data Set

These data can be used for various applications.  For example, they will provide 
meteorological input variables for a wide range of models.  Also, for those 
models that estimate fluxes, the data set provides flux data series for sensible 
and latent heat and CO2 for model verification.

13. Future Modifications and Plans

Once the data processing is complete, we will submit the convective and CO2 flux 
data for YJP in 1996 based on measurements from the ATI sonic.  Secondly, we are 
working on a more objective method to fill data gaps.  To date, we have used 
linear interpolation.  This method applies only to short periods, a few half-
hours at best, under steady-state conditions.  If the meteorological conditions 
are changing, linear interpolation fails.  It also fails if the data gap is 
longer than a few half-hours.  When we encountered a long data gap, we have left 
the data field blank and assigned a missing value placeholder.  Given that 
we did have significant gaps in the flux series because of the difficulties of 
the Campbell sonic in rainy weather, we have used ensemble averaging to create 
complete average diurnal curves of fluxes for publications.  We recognize that 
ensemble average data are not necessarily the ideal kind for modelers who prefer 
unbroken time series for each variable.

14. Software

14.1 Software Description

The measurement of the raw data was principally on Campbell Scientific data 
loggers, and all of the specific control programs for these data loggers are 
available. 

A variety of software was used in the data assessment and analysis.  STORAG, a 
Fortran program to find the minor heat storage terms in the energy balance, 
calculated the surface soil heat flux, the biomass heat storage, and the latent 
and sensible heat storage in the air up to the level of measurement of net 
radiation, where the surface balance was closed.  RADBAL, a Fortran program to 
solve the terms of the energy balance, was used in the analysis of the radiation 
balance data, including the calculation of shortwave and PPFD albedos, and the 
radiative surface temperatures.  We developed a number of QuattroPro 
spreadsheets for the calculation of convective fluxes (H and LE) and the CO2 
flux, including the correction of the fluxes for density effects and ensemble 
averaging to construct average daily flux patterns for the days included in the 
average.  Ensemble averaging was used as a means to find the mean diurnal 
pattern from often incomplete flux data series on individual days.  This 
methodology was successful and was favored over the development of other means 
for filling data gaps.  However, active research on the issue of how best to 
fill data gaps continues.

14.2 Software Access

All software developed for the analysis of the data is available by contacting 
J.H. McCaughey (PI).

15.   Data Access

15.1  Contact for Data Center/Data Access Information

These BOREAS data are available from the Earth Observing System Data and 
Information System (EOS-DIS) Oak Ridge National Laboratory (ORNL) Distributed 
Active Archive Center (DAAC). The BOREAS contact at ORNL is:

ORNL DAAC User Services
Oak Ridge National Laboratory
(865) 241-3952
ornldaac@ornl.gov
ornl@eos.nasa.gov

15.2  Procedures for Obtaining Data

BOREAS data may be obtained through the ORNL DAAC World Wide Web site at 
http://www-eosdis.ornl.gov/ or users may place requests for data by telephone, electronic mail, or fax.

15.3  Output Products and Availability

Requested data can be provided electronically on the ORNL DAAC's anonymous FTP 
site or on various media including, CD-ROMs, 8-MM tapes, or diskettes.

The complete set of BOREAS data CD-ROMs, entitled "Collected Data of the Boreal 
Ecosystem-Atmosphere Study", edited by Newcomer, J., et al., NASA, 1999, are 
also available.

16. Output Products and Availability

16.1 Tape Products

None.

16.2 Film Products

None.

16.3 Other Products

These data are available on the BOREAS CD-ROM series.

17. References 

17.1 Platform/Sensor/Instrument/Data Processing Documentation

All persons from Queens University, Kingston, Ontario, who worked on the flux 
towers received training on tower climbing techniques, tower rescue methods, and 
the operation of a safe field site.  The material is summarized in McCaughey 
(1993), and a summary of the training materials can be found in the tower safety 
document.

The data analysis to find the minor heat storage terms in the energy balance was 
accomplished with the software program titled STORAG, and details of this 
software are available in McCaughey (1991).

17.2 Journal Articles and Study Reports

Alemdag, I.S. 1983.  Mass equations and merchantability factors for Ontario 
softwoods.  Inf. Rep. PI-X-23, 27, Natl. For. Inst., Petawawa, Ontario, Canada.

Brand, D.G. 1987.  Estimating the surface area of spruce and pine foliage from 
displaced volume and length.  Can. J. For. Res. 17:1305-1308.

Campbell, G.S. and B.D. Tanner. 1985.  A krypton hygrometer for measurement of 
atmospheric water vapor concentration.  Moisture and Humidity 1985, Measurement 
and Control in Science and Industry, Proc. 1985 Intl. Symp. on Moisture and 
Humidity, Washington, DC, 609-612.

Campbell, G.S. and M.H. Unsworth. 1979.  An inexpensive sonic anemometer for 
eddy correlation.  J. Appl. Meteorol. 18:1072-1077.

Chen, J.M. and T.A. Black. 1992.  Foliage area and architecture of plant 
canopies from sunfleck size distributions.  Agric. For. Meteorol. 60:249-266.

Costello, A.M. 1995.  Canopy Characteristics and Surface-Atmosphere Interactions 
of a Young Jack Pine Forest Near Thompson, Manitoba, M.Sc. Thesis, Queens 
University, Kingston, Ontario, 125 pp.

Gower, S.T. and J.M. Norman. 1991.  Rapid estimation of leaf area index in 
conifer and broad-leaf plantations. Ecology 72:1896-1900.

Halliwell, D.H. and W.R. Rouse. 1987.  Soil heat flux in permafrost: 
Characteristics and accuracy of measurement. J. Climatol. 7:571-584.

Hodges, G.B. and E.A. Smith. 1997.  Intercalibration, objective analysis, inter-
comparison, and synthesis of BOREAS surface net radiation measurements.  Journal 
of Geophysical Research 102(D24):28,885-28,900.

Joiner, D.W. 1994.  Corrections to TF-10 eddy covariance fluxes.  Queens 
University internal report, 23 pp.

Lafleur, P.M., J.H. McCaughey, D.W. Joiner, P.A. Bartlett, and D.E. Jelinski. 
1997.  Seasonal trends in energy, water, and carbon dioxide fluxes at a northern 
boreal wetland.  Journal of Geophysical Research 102(D24):29,009-29,020.

Leclerc, M.Y. and G.W. Thurtell. 1990.  Footprint prediction of scalar fluxes 
using a Markovian analysis. Boundary-Layer Meteorol. 52:247-258.

Leuning, R. and J. Moncrieff. 1990.  Eddy-covariance CO2 flux measurement using 
open- and closed-path CO2 analyzers: Corrections for analyzer water vapor 
sensitivity and damping of fluctuations in air sampling tubes.  Boundary-Layer 
Meteorol. 53:63-76.

Leuning, R. and K.M. King. 1992.  Comparison of eddy-covariance measurements of
CO2 fluxes by open- and closed-path CO2 analyzers.  Boundary-Layer Meteorol. 
59:297-311.

McCaughey, J.H. 1991.  Safety in Climatology: a Seminar on Tower Climbing.  7 
pp., 1987, last revision in 1993.

McCaughey, J.H. RTDMS Program Manual, Second Edition, Delta T Documents, 50 pp.

McCaughey, J.H. and W.L. Saxton. 1988.  Energy balance storage terms in a mixed 
forest.  Agric. For. Meteorol. 44:1-18.

McCaughey, J.H., P.M. Lafleur, D.W. Joiner, P.A. Bartlett, A.M. Costello, D.E. 
Jelinski, and M.G. Ryan. 1997.  Magnitudes and seasonal patterns of energy, 
water, and carbon exchanges at a boreal young jack pine forest in the BOREAS 
northern study area.  Journal of Geophysical Research 102(D24):28,997-29,008.

Mueller-Dombois, D. and H. Ellenberg. 1974.  Aims and Methods of Vegetation 
Ecology.  J. Wiley & Sons, New York, 547 pp.

Saxton, W.L. and J.H. McCaughey. 1988.  Measurement considerations and trends in 
biomass heat storage of a mixed forest.  Can. J. For. Res. 18:143-149.

Schmid, H.P. and T.R. Oke. 1990.  A model to estimate the source area 
contributing to turbulent exchange in the surface layer over patchy terrain.  
Quart. J. Roy. Meteorol. Soc. 116:965-988.

Sellers, P. and F. Hall. 1994. Boreal Ecosystem-Atmosphere Study: Experiment 
Plan. Version 1994-3.0, NASA BOREAS Report (EXPLAN 94).

Sellers, P. and F. Hall. 1996. Boreal Ecosystem-Atmosphere Study: Experiment 
Plan. Version 1996-2.0, NASA BOREAS Report (EXPLAN 96).

Sellers, P., F. Hall, and K.F. Huemmrich. 1996. Boreal Ecosystem-Atmosphere 
Study: 1994 Operations. NASA BOREAS Report (OPS DOC 94).

Sellers, P., F. Hall, and K.F. Huemmrich. 1997. Boreal Ecosystem-Atmosphere 
Study: 1996 Operations. NASA BOREAS Report (OPS DOC 96).

Sellers, P., F. Hall, H. Margolis, B. Kelly, D. Baldocchi, G. den Hartog, J. 
Cihlar, M.G. Ryan, B. Goodison, P. Crill, K.J. Ranson, D. Lettenmaier, and D.E.
Wickland. 1995. The boreal ecosystem-atmosphere study (BOREAS): an overview and 
early results from the 1994 field year. Bulletin of the American
Meteorological Society. 76(9):1549-1577.

Sellers, P.J., F.G. Hall, R.D. Kelly, A. Black, D. Baldocchi, J. Berry, M. Ryan, 
K.J. Ranson, P.M. Crill, D.P. Lettenmaier, H. Margolis, J. Cihlar, J.
Newcomer, D. Fitzjarrald, P.G. Jarvis, S.T. Gower, D. Halliwell, D. Williams, B. 
Goodison, D.E. Wickland, and F.E. Guertin. 1997. BOREAS in 1997:
Experiment overview, scientific results, and future directions. Journal of 
Geophysical Research 102(D24):28731-28769.

Smith, E.A., G.B. Hodges, M. Bacrania, H.J. Cooper, M.A. Owens, R. Chappell, and 
W. Kincannon. 1997.  Final Report NASA Grant NAG5-2447, BOREAS Net Radiometer 
Engineering Study.  Goddard Space Flight Center, Greenbelt, Maryland. 51 pp.

Smith, N.J., J.M. Chen, and T.A. Black. 1993.  Effects of clumping on estimates 
of stand leaf area index using the LI-COR LAI 2000.  Can. J. For. Res. 23:1940-
1943.

Tanner, B.T., E. Swiatek, and J.P. Greene. 1993.  Density fluctuations and use 
of the krypton hygrometer in surface flux measurements.  Proceedings of the 1993 
National Conference on Irrigation and Drainage Engineering, American Society of 
Civil Engineers, Park City, Utah.

Thom, A.S. 1975.  Momentum, mass and heat exchange of plant communities. In: 
Vegetation and the Atmosphere, Vol. 1 (Ed. J. L. Monteith), Academic Press, 
London.  pp. 57-109.

Webb, E.K. 1982.  On the correction of flux measurements for effects of heat and 
water vapor transfer.  Boundary-Layer Meteorol. 23:251-254.
 
Webb, E.K., G.I. Pearman, and R. Leuning. 1980.  Correction of flux measurements 
for density effects due to heat and water vapor transfer.  Quart. J. Roy. 
Meteorol. Soc. 106:85-100.

17.3 Archive/DBMS Usage Documentation

None.

18. Glossary of Terms

Symbol       Quantity                                       Units

a            Albedo                                         dim.
AT           Total needle area                              cm2
C            Volumetric heat capacity of soil               J/(m3 C)
C'           CO2 concentration per volume fluctuation       ppmv
CF           Correction factor                              dim.
Cm           Heat capacity of mineral fraction              J/(m3 C)
Co           Heat capacity of organic soil                  J/(m3 C)
CO2night     Net CO2 flux from model when Kd<5 W/m^2        umol/(m2 s1)
CON          Constant used in STORAG to find heat  
             storage in air, soil, and vegetation           J/(m3 C1 s1)                                        
Cp           Specific heat of air at constant pressure      J/(kg C)
Cw           Heat capacity of water                         J/(m^3 C)
dbh          Diameter at breast height                      cm
de           Rate of change in vapor pressure               kPa/s
dim.         Dimensionless number                           dim.
DS           Depth of temperature measurements              m         
dTa          Rate of change in air temperature              C/s
dTb          Rate of change in biomass temperature          C/s
dTs          Rate of change in soil temperature             C/s
FeCO2        Eddy flux of CO2                               umol/(m2 s1) or
              (equivalent to net flux at height of          mg/(m2 s2)
               measurement)                                      
FsCO2        Storage flux of CO2                            mol/(m2 s1)
FCO2         Total CO2 flux                                 mol/(m2 s^)
G            Soil heat flux at surface                      W/m2
G(z)         Soil heat flux measured at depth z             W/m2
G10          Heat storage in the soil volume above
              10-cm depth                                   W/m2
Ga           Sensible heat storage in air                   W/m2
GB           Heat flux out the bottom of the soil profile
              at the fen                                    W/m2
Gcal         Total heat storage in the soil profile at fen  W/m2
Ge           Latent heat storage in air                     W/m2
Gfen         Ground heat flux at the fen in 1994            W/m2
Ghol         Ground heat flux in hollow at the fen          W/m2
G(z)n        Soil heat flux at YJP (north site)             W/m2
Gpla         Time-integrated soil flux from plate at fen    W/m2
G(z)w        Soil heat flux at YJP (west site)              W/m2
G_total      Total heat storage                             W/m2
G_totaln     Total heat storage at YJP (north site)         W/m2
G_totalw     Total heat storage at YJP (west site)          W/m2
Gveg         Heat storage in biomass at YJP                 W/m2
Gvegn        Heat storage in biomass at YJP (north site)    W/m2
Gvegw        Heat storage in biomass at YJP (west site)     W/m2
h            Tree height                                    m
H            Sensible heat flux                             W/m2
HCS          Heat capacity of soil in STORAG                J/(m3 C1)
Kd           Incoming solar radiation                       W/m2 
Ku           Reflected solar radiation                      W/m2
Ks           Thermal conductivity of saturated peat soil    W/(m1 K1)
k            Instrument H2O vapor absorption coefficient    m3/(kg1 cm1)
K*           Total shortwave radiation                      W/m2
L            Latent heat of vaporization of water           J/kg
LE           Latent heat flux                               W/m2
Ld           Incoming longwave radiation                    W/m2
Lu           Outgoing longwave radiation                    W/m2
L*           Net longwave radiation                         W/m2
M            Molecular weight of dry air                    Mole
mis.         Missing value                                  dim.
Mv           Standing green biomass                         kg/m2
P            Atmospheric pressure                           kPa
PA           Total projected needle area                    cm2
PA(S)        Shoot projected area                           cm2
PPFDd        Incoming PPFD                                  mol/(m2 s1)
PPFDu        Reflected PPFD                                 mol/(m2 s1) 
Qd           Total incoming radiation                       W/m2
QGZ          Soil heat flux from flux plate
              (for STORAG only)                             W/m2
Qu           Total outgoing radiation                       W/m2
Q*           Net radiation                                  W/m2
Q*corr       Corrected net radiation (following             W/m2
              Hodges and Smith (1997))
q            Water vapor density                            g/m3
q'           Water vapor density fluctuation                g/m3
R            Universal gas constant                         J/(mol1 K1)
R           Conifer correction factor                      dim.
rho          Density of air                                 kg/m3
rho(c)       Density of CO2                                 kg/m3
s            Signal voltage from hygrometer                 mv
S            Flux equivalent to the heat stored between     W/m2
             individual soil layers
SH           Specific humidity                              g/kg
sSH          Standard deviation of specific humidity        g/kg
T'           Temperature fluctuation                        C
T_air        Air temperature                                C
TB           Biomass temperature in STORAG                  C
Tblw         Stem temperature of large trees (west site)    C
Tbmw         Stem temperature of medium trees (west site)   C
Tbsn         Stem temperature of small trees (north site)   C
Tbsw         Stem temperature of small trees (west site)    C
TD           Dry bulb temperature in STORAG                 C
TOL          Thickness of organic layer in STORAG           m
Ts           Soil temperature                               C
Ts10avg      Average soil temperature at 10-cm depth        C
Ts75avg      Average soil temperature at 75-cm depth        C
TW           Wet-bulb temperature                           C
U            Wind speed                                     m/s
v            Intercept of the krypton hygrometer
              calibration                                   mv
w'           Vertical wind velocity                         m/s
x            Path length of the hygrometer                  cm
Xm           Soil volumetric mineral fraction               fraction
Xo           Soil volumetric organic soil fraction          fraction
Xw           Soil volumetric water fraction                 fraction
XW           Soil moisture content in STORAG                fraction
z            Depth to soil heat flux plate                  m
ZCQ          Control variable in STORAG; used to read
             two variables: height of canopy and height
             of net pyrradiometer                           m,m
zr           Reference height                               m
ZR           Height of net radiation measurement
              in early version of STORAG                    m

19. List of Acronyms

    AES     Atmospheric Environment Services
    AFM-07  Airborne Fluxes and Meteorology Group 7 in BOREAS
    ASCII   American Standard Code for Information Interchange
    ATI     Applied Techologies, Inc.
    BOREAS  BOReal Ecosystem-Atmosphere Study 
    BORIS   BOREAS Information System
    CCRS    Canada Centre for Remote Sensing
    CD-ROM  Compact Disk-Read-Only Memory
    CGR     Certified by Group
    CO2     Carbon dioxide
    CPI     Certified by PI
    CPI-??? Certified but questionable
    DAAC    Distributed Active Archive Center
    DC      Direct Current
    DOY     Day of Year
    ENBAL   Energy Balance (analysis program)
    EOS     Earth Observing System
    EOSDIS  EOS Data and Information System
    Fen     Fen wetland site
    FFC     Focused Field Campaign
    FPAR    Fraction of PPFD absorbed by the vegetation canopy
    GMT     Greenwich Mean Time
    GPS     Global Positioning System
    GSFC    Goddard Space Flight Center
    HTML    HyperText Markup Language
    HYD-01  Hydrology Group 1 in BOREAS
    IRGA    Infrared Gas Analyzer
    LAI     Leaf Area Index
    LW      Longwave
    MV      Mass of Vegetation
    N/A     Not available
    NAD83   North American Datum of 1983
    NARC    National Atmospheric Radiation Center
    NASA    National Aeronautics and Space Administration
    NEE     Net Ecosystem Exchange
    NOAA    National Oceanic and Atmospheric Administration
    NSA     Northern Study Area
    ORNL    Oak Ridge National Laboratory
    PANP    Prince Albert National Park
    PAR     Photosynthetically Active Radiation
    PCQM    Point Center Quarter Method
    PPFD    Photosynthetic Photon Flux Density
    PNFI    Petawawa National Forest Institute
    RADBAL  Radiation Balance (analysis program)
    REBS    Radiation Energy Balance Systems, Inc.
    RH      Relative humidity
    RSS-07  Remote Sensing Science Group 7 in BOREAS
    SRC     Saskatchewan Research Council
    SB      Short, below breast height
    SCF     Shoot Clumping Factor
    STORAG  (heat) storage (analysis program)
    SVAT    Soil-Vegetation-Atmosphere-Transfer
    SW      Shortwave
    TA      Tall, above breast height
    TB      Tall, below breast height
    TF-10   Tower Flux group 10
    URL     Uniform Resource Locator
    UTC     Universal Time Coordinated
    UTM     Universal Transverse Mercator
    WAB     Wind Aligned Blob
    WPL     Webb, Pearman, and Leuning flux correction
    YJP     Young Jack Pine forest site

20. Document Information

20.1 Document Revision Date

     Written: 06-Jun-1998
     Revised: 25-May-1999

20.2 Document Review Date(s)

     BORIS Review:  25-Apr-1999
     Science Review:

20.3 Document ID

20.4  Citation

When using these data please include the following acknowledgment:

These data were provided by BOREAS Team TF-10; the primary consultants 
include:
Flux and meteorological data (YJP and Fen):
Dr. J. Harry McCaughey, Department of Geography, Queen's University, Kingston, 
ON, CANADA, K7L 3N6 (PI)
and
Dr. Peter M. Lafleur, Department of Geography, Trent University, Peterborough, 
ON, CANADA, K9J 7B8
Both investigators should be acknowledged in all future publications.
Fen biophysical data: Dr. D.E. Jelinski, Department of Geography, Queen's 
University, Kingston, ON, CANADA, K7L 3N6 (PI)
YJP biophysical data: Dr. J. Harry McCaughey, Department of Geography, Queen's 
University, Kingston, ON, CANADA, K7L 3N6 (PI);
as well as citations of relevant papers (see Section 17.2).

If using data from the BOREAS CD-ROMs, please also reference the data as:
McCaughey, J.H. and Dennis E. Jelinski,"Surface Energy and Water Balances of 
Forest and Wetland Subsystems in the Boreal Forest - Surface Atmosphere Links 
and Ecological Controls." in Collected Data of The Boreal Ecosystem-Atmosphere 
Study. Eds. J. Newcomer, D. Landis, S. Conrad, S. Curd, K. Huemmrich, D. Knapp, 
A. Morrell, J. Nickeson, A. Papagno, D. Rinker, R. Strub, T. Twine, F. Hall, and 
P. Sellers.  CD-ROM. NASA, 2000.

To cite the BOREAS CD-ROM set as a published volume, use:
J. Newcomer, D. Landis, S. Conrad, S. Curd, K. Huemmrich, D. Knapp, A. Morrell, 
J. Nickeson, A. Papagno, D. Rinker, R. Strub, T. Twine, F. Hall, and P. Sellers, 
eds. Collected Data of The Boreal Ecosystem-Atmosphere Study.  CD-ROM. NASA, 
2000.

20.5 Document Curator

20.6 Document URL

Keywords:

ALBEDO
BOWEN RATIO
CARBON DIOXIDE FLUX
CLIMATE CHANGE
ENERGY BALANCE
EVAPOTRANSPIRATION
FEN
JACK PINE
LATENT HEAT FLUX
NET ECOSYSTEM EXCHANGE
RADIATION BALANCE
SENSIBLE HEAT FLUX
STOMATAL CONDUCTANCE
STOMATAL RESISTANCE
SVAT
TF10_NSA-YJP_Flux.doc
06/09/99