Mahrt, L., D. Vickers, J. Sun, and J. H. McCaughey. 2001. BOREAS Follow-On FLX-03 Area-Averaged Flux Data for the NSA and SSA. Data set. Available on-line [http://www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.
1.2 Data Set Introduction
Area-averaged fluxes were calculated
using flux data extracted from the BOReal Ecosystem-Atmosphere Study (BOREAS)
Information System (BORIS) as part of the follow-on activities. Data for
the period of 1-June-1994 through 30-September-1994 for the Southern Study
Area (SSA) and the Northern Study Area (NSA) were used in 1994. In 1996,
measurement made from 31-May through 29-September in the SSA were used.
1.3 Objective/Purpose
The objective of this research were
to fulfill the need for area-averaged flux data in the BOREAS region.
1.4 Summary of Parameters
Date (day)
Hour of Day (hour)
Sensible Heat Flux (W/m2)
Latent Heat Flux (W/m2)
Net Radiation (W/m2)
CO2 Flux (mg/m2/s)
1.5 Discussion
Data were taken from raw Canadian Twin
Otter Aircraft data and tower data from all of the sites from the BOREAS
information system. Fluxes are used from the highest tower level at each
site. One flux tower was implemented for each of the major vegetation types.
For the Young Jack Pine site, the Campbell sonic anemometer was selected.
The area-averaged fluxes are estimated
as the sum of the fluxes over each vegetation type, weighted according
to the fractional coverage of that vegetation type and modified by adjustments
discussed below. (See equation 1) A more detailed document is available
from mahrt@oce.orst.edu.
The area-averaged fluxes, [Fphi],
are estimated by:
[Fphi] = Ii=1 * alphai * Wi * Fphi,i (1)
where phi is the vertically transported variable such as potential temperature
or moisture, the brackets denote spatial averaging, Fphi,i is
the tower flux for the ith surface type, alphai represent
corrections for the tower data for the ith surface type and
Wi is the fractional coverage for the ith surface
type.
A tower cannot be completely representative
of the area-averaged flux because of spatial variations even within a given
vegetation type and because towers for wet surface types are sometimes
located in drier areas for practical reasons. In the latter case, the aircraft
measured less sensible heat flux and greater latent heat flux compared
to the tower (Desjardins et al., 1997). As a result, the Bowen ratio for
the aircraft data were substantially smaller than the tower Bowen ratio
for some sites. Table 1 shows the Bowen ratio for the aircraft and tower
data computed from the sensible and latent heat fluxes averaged over all
the periods with aircraft passes over a given tower. One could impose the
average aircraft Bowen ratio on the tower data. However, this procedure
would remove seasonal and synoptic changes in the Bowen ratio. Instead,
we adjust the tower Bowen ratio downward by a fixed fraction (adjustment
factor, Table 1). The tower latent and sensible heat fluxes for each observation
are then adjusted (augmented latent heat flux and reduced sensible heat
flux) to match the adjusted Bowen ratio while preserving the sum of the
tower sensible and latent heat fluxes. The Bowen ratio adjustment is applied
only to daytime periods when the net radiation, sensible heat flux and
latent heat flux are all upward.
TABLE 1: Bowen ratios for sites with adequate aircraft data and adjustment factor
Surface Type | Aircraft | Tower | adj. factor |
---|---|---|---|
old aspen SSA |
|
|
|
old black spruce SSA |
|
|
|
old Jack Pine SSA |
|
|
|
young jack pine NSA |
|
|
|
old black spruce NSA |
|
|
|
old jack pine NSA |
|
|
|
Two sets of fractional coverages are used. The primary set is based
on Hall et al. (1997). To study the sensitivity to exact geographical location,
we also use a set of values from Desjardins et al. (1997) that are based
on a part of the SSA where grid flights were flown. This area contained
substantially more conifer and less aspen compared to the entire SSA.
Based on 1994 Landsat TM using bands
2 (red), 4 (infrared) and 5 (mid-infrared), Hall et al. (1997) identified
13 classes of surface type. To proceed, we must translate the thirteen
classes into the categories based on the five available towers plus the
water category (Table 2). We assume that all deciduous, regeneration deciduous
and medium age deciduous are aspen, wet conifer is black spruce, dry conifer
is jack pine, mixed is half aspen and half black spruce and new generation
and medium age regeneration conifer are pro-rated between black spruce
and jack pine. The June 1994 Landsat image omitted 12% of the eastern part
of the SSA. Fractional coverages for this part of the domain were estimated
from Chen et al. (1999). As a final adjustment, the fractional coverage
of the fen is thought to be substantially higher than the originally reported
8%. We have augmented the value to 13% and decreased the other non-water
fractional coverages in proportion. The final values of fractional coverage
are listed in Table 2.
TABLE 2: Fractional coverages
Class | Hall et al., adjusted | Desjardins et al. |
---|---|---|
Black spruce |
|
|
Jack Pine |
|
|
Aspen |
|
|
Fen |
|
|
Water |
|
|
The area-averaged fluxes are highly correlated to the net radiation, underscoring the need for models to correctly predict the cloud cover; the noon-time relationship between area-averaged fluxes and net radiation is shown in Figure 1. The relationship between area-averaged fluxes and area-averaged net radiation is a little stronger than the relationship at individual locations.
Figure 1. Area-averaged fluxes versus area-averaged net radiation for noon local time for a) sensible and b) latent heat fluxes. |
Figure 2. Area-averaged fluxes using the fractional coverages from Hall et al. (1997) versus those using Desjardins et al. (1997) for noon local time for a) sensible and b) latent heat fluxes. |
Figure 4 reveals the influence of the adjustment of the net radiation
based on Hodges and Smith (1997) for observations at noon, which are small
partly because of cancellation in the area average (Section 3.2). Figure
5 shows that the adjustment of the Bowen ratio increases the noon-time
area-averaged latent heat flux by about 6% and decreases the area-averaged
moisture flux by about 6%. Notice that the comparisons between different
versions of the noon-time area-averaged fluxes (Figures 2 and 5) show much
more variation along the one-to-one line compared to the deviations from
the one-to-one line. This implies that predicting the cloud cover and net
radiation is the single most important step in assessing area-averaged
fluxes.
Some investigators maintain that fluxes
can be improved by forcing them to balance the surface energy budget. This
adjustment assumes that the errors in the surface energy imbalance are
due mainly to the eddy correlation estimate of the heat and moisture fluxes
and that the estimates of the net radiation and soil heat flux are approximately
correct. The usual procedure is to increase the sensible and latent heat
fluxes proportionally to preserve the Bowen ratio. That is, the total of
the sensible and latent heat fluxes is increased to balance the surface
energy budget without modifying the Bowen ratio.
Figure 6. Adjustments of the flux by balancing the surface energy budget. |
1.6 Related Data Sets
BOREAS AFM-04 Twin Otter Aircraft Flux Data
BOREAS AFM-11 Aircraft Flux Analysis Reports
BOREAS AFM-13 Aircraft Flux Analyses
BOREAS TF-01 SSA-OA Tower Flux, Meteorological, and Soil Temperature
Data
BOREAS TF-02 SSA-OA Tower Flux, Meteorological, and Precipitation Data
BOREAS TF-03 Automated Chamber CO2 Flux Data From The NSA-OBS Data
BOREAS TF-03 Tower Flux & Meteorological Data
BOREAS TF-04 SSA-YJP Tower Flux, Meteorological, and Canopy Condition
Data
BOREAS TF-05 Tower Flux & Meteorological Data
BOREAS TF-06 SSA-YA Surface Energy Flux and Meteorological Data
BOREAS TF-07 SSA-OBS Tower Flux and Meteorological Data
BOREAS TF-08 NSA-OJP Tower Flux, Meteorological, and Soil Temperature
Data
BOREAS TF-09 SSA-OBS Tower Flux, Meteorological, and Soil Temperature
Data
BOREAS TF-10 NSA-Fen Tower Flux And Meteorological Data
BOREAS TF-10 NSA-YJP Tower Flux, Meteorological, and Porometry Data
BOREAS TF-11 SSA-Fen Tower Flux and Meteorological Data
2.2 Title of Investigation
Spatially-averaged fluxes of CO2,
heat, and moisture
2.3 Contact Information
Contact 1:
L. Mahrt
Oregon State University
Corvallis, OR
mahrt@oce.orst.edu
Contact 2:
Dean Vickers
Oregon State University
Corvallis, OR
Contact 3:
Jielun Sun
National Center for Atmospheric Research
Boulder, CO
jsun@ucar.edu
Contact 4:
J. Harry McCaughey
Queen's University
Kingston, Ontario, Canada
mccaughe@post.queensu.ca
Contact 5:
Andrea Papagno
Raytheon ITSS
NASA GSFC
Greenbelt, MD
(301) 286-3134
(301) 286-0239 (fax)
Andrea.Papagno@gsfc.nasa.gov
4.1.1 Collection Environment
These data were extracted from the BORIS Information System using the following data sets: (with the exception of the soil temperature and precipitation data)BOREAS AFM-04 Twin Otter Aircraft Flux Data
BOREAS AFM-11 Aircraft Flux Analysis Reports
BOREAS AFM-13 Aircraft Flux Analyses
BOREAS TF-01 SSA-OA Tower Flux, Meteorological, and Soil Temperature Data
BOREAS TF-02 SSA-OA Tower Flux, Meteorological, and Precipitation Data
BOREAS TF-03 Automated Chamber CO2 Flux Data From The NSA-OBS Data
BOREAS TF-03 Tower Flux & Meteorological Data
BOREAS TF-04 SSA-YJP Tower Flux, Meteorological, and Canopy Condition Data
BOREAS TF-05 Tower Flux & Meteorological Data
BOREAS TF-06 SSA-YA Surface Energy Flux and Meteorological Data
BOREAS TF-07 SSA-OBS Tower Flux and Meteorological Data
BOREAS TF-08 NSA-OJP Tower Flux, Meteorological, and Soil Temperature Data
BOREAS TF-09 SSA-OBS Tower Flux, Meteorological, and Soil Temperature Data
BOREAS TF-10 NSA-Fen Tower Flux And Meteorological Data
BOREAS TF-10 NSA-YJP Tower Flux, Meteorological, and Porometry Data
BOREAS TF-11 SSA-Fen Tower Flux and Meteorological Data4.1.2 Source/Platform
We used raw Canadian Twin Otter Aircraft data and used tower data from all of the sites (highest level only) from the BOREAS information system. See Section 4.1.1 for more details.4.1.3 Source/Platform Mission Objectives
See Section 4.1.3 in the documentation for the data sets listed in Section 4.1.1.4.1.4 Key Variables
Sensible Heat Flux (W/m2)
Latent Heat Flux (W/m2)
Net Radiation (W/m2)
CO2 Flux (mg/m2/s)4.1.5 Principles of Operation
See Section 4.1.5 in the documentation for the data sets listed in Section 4.1.1.4.1.6 Sensor/Instrument Measurement Geometry
See Section 4.1.6 in the documentation for the data sets listed in Section 4.1.1.4.1.7 Manufacturer of Sensor/Instrument
See Section 4.1.7 in the documentation for the data sets listed in Section 4.1.1.
4.2 Calibration
4.2.1 SpecificationsReturn to top of document.
See Section 4.2.1 in the documentation for the data sets listed in Section 4.1.1.4.2.1.1 Tolerance
See Section 4.2.1.1 in the documentation for the data sets listed in Section 4.1.1.
4.2.2 Frequency of Calibration
See Section 4.2.2 in the documentation for the data sets listed in Section 4.1.1.4.2.3 Other Calibration Information
See Section 4.2.3 in the documentation for the data sets listed in Section 4.1.1.
6.2 Field Notes
See Section 6.2 in the documentation
for the data sets listed in Section 4.1.1.
7.1.1 Spatial Coverage
The measurement sites and associated North American Datum of 1983 (NAD83) coordinates are:Operational UTM UTM UTM Site Grid ID Latitude Longitude Zone Northing Easting ------------- --------- ---------- ----------- ---- --------- -------- SSA-9OA-FLXTR C3B7T 53.62889°N 106.19779°W 13 5942899.9 420790.5 SSA-YJP-FLXTR F8L6T 53.87581°N 104.64529°W 13 5969762.5 523320.2 SSA-OJP-FLXTR G2L3T 53.91634°N 104.69203°W 13 5974257.5 520227.7 SSA-OBS-FLXTR G8I4T 53.98717°N 105.11779°W 13 5982100.5 492276.5 NSA-OBS-FLXTR T3R8T 55.88007°N 98.48139°W 14 6192853.4 532444.5 NSA-OJP-FLXTR T7Q8T 55.92842°N 98.62396°W 14 6198176.3 523496.2 NSA-YJP-FLXTR T8S9T 55.89575°N 98.28706°W 14 6194706.9 544583.9 SSA-ASP-AUX02 B9B7A 53.59098°N 106.18693°W 13 5938447.2 421469.8 SSA-9BS-AUX01 D0H6S 53.64877°N 105.29534°W 13 5944263.4 480508.7 SSA-ASP-AUX03 D6L9A 53.66879°N 104.6388°W 13 5946733.2 523864 SSA-ASP-AUX05 D9G4A 53.74019°N 105.46929°W 13 5954718.4 469047.1 SSA-ASP-AUX06 E7C3A 53.84741°N 106.08112°W 13 5966863.1 428905.9 SSA-MIX-AUX01 F1N0M 53.80594°N 104.533°W 13 5962031.8 530753.7 SSA-9JP-AUX02 F5I6P 53.86608°N 105.11175°W 13 5968627.1 492651.3 SSA-9JP-AUX04 F7J0P 53.88336°N 105.05115°W 13 5970323.3 496667 SSA-9JP-AUX03 F7J1P 53.88211°N 105.03226°W 13 5970405.6 497879.4 SSA-9JP-AUX05 G1K9P 53.9088°N 104.74812°W 13 5973404.5 516546.7 SSA-9BS-AUX03 G2I4S 53.93021°N 105.13964°W 13 5975766.3 490831.4 SSA-9BS-AUX02 G2L7S 53.90349°N 104.63785°W 13 5972844.3 523793.6 SSA-MIX-AUX02 G4I3M 53.9375°N 105.14246°W 13 5976354.9 490677.3 SSA-9JP-AUX06 G4K8P 53.91883°N 104.76401°W 13 5974516.6 515499.1 SSA-9BS-AUX04 G6K8S 53.94446°N 104.759°W 13 5977146.9 515847.9 SSA-9JP-AUX07 G7K8P 53.95882°N 104.77148°W 13 5978963.8 514994.2 SSA-9JP-AUX08 G8L6P 53.96558°N 104.63755°W 13 5979752.7 523778 SSA-9BS-AUX05 G9I4S 53.99877°N 105.11805°W 13 5983169.1 492291.2 SSA-9JP-AUX09 G9L0P 53.97576°N 104.73779°W 13 5980856 517197.7 SSA-9BS-AUX06 H1E4S 54.04093°N 105.73581°W 13 5988326.1 451815.7 SSA-MIX-AUX03 H2D1M 54.06535°N 105.92706°W 13 5991190.3 439327.7 SSA-9BS-AUX07 H2D1S 54.06199°N 105.92545°W 13 5990814.4 439428.1 SSA-MIX-AUX04 H3D1M 54.066°N 105.92982°W 13 5991042.3 439178.4 SSA-9JP-AUX10 I2I8P 54.11181°N 105.05107°W 13 5995963.1 496661.4 NSA-ASP-AUX01 P7V1A 55.50253°N 98.07478°W 14 6151103.7 558442.1 NSA-MIX-AUX01 Q1V2M 55.54568°N 98.03769°W 14 6155937.3 560718.3 NSA-9JP-AUX01 Q3V3P 55.55712°N 98.02473°W 14 6157222.2 561517.9 NSA-ASP-AUX03 R8V8A 55.67779°N 97.8926°W 14 6170774.8 569638.4 NSA-9BS-AUX01 S8W0S 55.76824°N 97.84024°W 14 6180894.9 572761.9 NSA-ASP-AUX05 S9P3A 55.88576°N 98.87621°W 14 6193371.6 507743.3 NSA-MIX-AUX02 T0P5M 55.88911°N 98.85662°W 14 6193747.3 508967.7 NSA-9BS-AUX08 T0P7S 55.88371°N 98.82345°W 14 6193151.1 511043.9 NSA-9BS-AUX07 T0P8S 55.88351°N 98.80225°W 14 6193132 512370.1 NSA-9BS-AUX02 T0W1S 55.78239°N 97.80937°W 14 6182502 574671.7 NSA-9OA-9TETR T2Q6A 55.88691°N 98.67479°W 14 6193540.7 520342 NSA-9BS-AUX03 T3U9S 55.83083°N 97.98339°W 14 6187719.2 563679.1 NSA-ASP-AUX04 T4U5A 55.84757°N 98.04329°W 14 6189528.2 559901.6 NSA-9BS-AUX05 T4U8S 55.83913°N 97.99325°W 14 6188633.4 563048.2 NSA-9BS-AUX04 T4U9S 55.83455°N 97.98364°W 14 6188132.8 563657.5 NSA-9BS-AUX14 T5Q7S 55.9161°N 98.64022°W 14 6196800.5 522487.2 NSA-9BS-9TETR T6R5S 55.90802°N 98.51865°W 14 6195947 530092 NSA-9BS-AUX06 T6T6S 55.87968°N 98.18658°W 14 6192987.9 550887.9 NSA-9BS-AUX13 T7R9S 55.91506°N 98.44877°W 14 6196763.6 534454.5 NSA-9JP-AUX03 T7S9P 55.89486°N 98.30037°W 14 6194599.1 543752.4 NSA-9BS-AUX09 T7T3S 55.89358°N 98.22621°W 14 6194505.6 548391.8 NSA-9JP-AUX06 T8Q9P 55.93219°N 98.6105°W 14 6198601.4 524334.5 NSA-ASP-AUX07 T8S4A 55.91856°N 98.37041°W 14 6197194.6 539348.3 NSA-9BS-AUX15 T8S4S 55.91689°N 98.37111°W 14 6197008.6 539306.4 NSA-9JP-AUX04 T8S9P 55.90456°N 98.28385°W 14 6195688.9 544774.3 NSA-9JP-AUX05 T8T1P 55.90539°N 98.26269°W 14 6195795.3 546096.3 NSA-9JP-AUX07 T9Q8P 55.93737°N 98.59568°W 14 6199183.2 525257.1 NSA-9BS-AUX10 U5W5S 55.9061°N 97.70986°W 14 6196380.8 580655.5 NSA-9BS-AUX12 U6W5S 55.91021°N 97.70281°W 14 6196846.5 581087.8 NSA-ASP-AUX08 V5X7A 55.97396°N 97.48565°W 14 6204216.6 594506.1 NSA-ASP-AUX09 W0Y5A 56.00339°N 97.3355°W 14 6207706.6 603796.6 NSA-9JP-AUX02 99O9P 55.88173°N 99.03952°W 14 6192917.5 497527.8 NSA-ASP-AUX02 Q3V2A 55.56227°N 98.02635°W 14 6157793.5 561407.9 SSA-MIX-9TETR D9I1M 53.7254°N 105.20643°W 13 5952989.7 486379.7 SSA-OJP-FLXTR G2L3T 53.91634°N 104.69203°W 13 5974257.5 520227.77.1.2 Spatial Coverage Map
See Section 7.1.2 in the documentation for the data sets listed in Section 4.1.1.7.1.3 Spatial Resolution
See Section 7.1.3 in the documentation for the data sets listed in Section 4.1.1.7.1.4 Projection
See Section 7.1.4 in the documentation for the data sets listed in Section 4.1.1.7.1.5 Grid Description
See Section 7.1.5 in the documentation for the data sets listed in Section 4.1.1.
7.2 Temporal Characteristics
7.2.1 Temporal Coverage
Data are provided between the period of 1-June-1994 through 30-September-1994 for the SSA and the NSA. In 1996, the coverage period is from 31-May through 29-September in the SSA.7.2.2 Temporal Coverage Map
Not available.7.2.3 Temporal Resolution
None given.
7.3 Data Characteristics
7.3.1 Parameter/Variable
The parameters contained in the data files are:Column Name ------------------------------ SITE_ID DATE_OBS TIME_OBS_LOCAL INDEX_NUM SENSIBLE_HEAT_FLUX LATENT_HEAT_FLUX NET_RADIATION CO2_FLUX CRTFCN_CODE REVISION_DATE7.3.2 Variable Description/Definition
The descriptions of the parameters contained in the data files are:Column Name Description ------------------------------ -------------------------------------- SITE_ID The identifier assigned to the site by BOREAS, in the format SSS-TTT-CCCCC, where SSS identifies the portion of the study area: NSA, SSA, REG, TRN, and TTT identifies the cover type for the site, 999 if unknown, and CCCCC is the identifier for site, exactly what it means will vary with site type. DATE_OBS The date on which the data were collected. TIME_OBS_LOCAL The Local Time (Local) when the data were collected. INDEX_NUM The index number of the observation. SENSIBLE_HEAT_FLUX The sensible heat flux LATENT_HEAT_FLUX The latent heat flux NET_RADIATION The net radiation CO2_FLUX The carbon dioxide flux CRTFCN_CODE The BOREAS certification level of the data. Examples are CPI (Checked by PI), CGR (Certified by Group), PRE (Preliminary), and CPI-??? (CPI but questionable). REVISION_DATE The most recent date when the information in the referenced data base table record was revised7.3.3 Unit of Measurement
The measurement units for the parameters contained in the data files are:Column Name Units ------------------------------ ------------------------------------------------ SITE_ID [none] DATE_OBS [DD-MON-YY] TIME_OBS_LOCAL [HHMM Local] INDEX_NUM [none] SENSIBLE_HEAT_FLUX [Watts][meter^-2] LATENT_HEAT_FLUX [Watts][meter^-2] NET_RADIATION [Watts][meter^-2] CO2_FLUX [micromoles][meter^-2][second^-1] CRTFCN_CODE [none] REVISION_DATE [DD-MON-YY]7.3.4 Data Source
The source of the parameter values contained in the data files is:Column Name Data Source ------------------------------ ------------------------------------------------ SITE_ID [Assigned by BORIS] DATE_OBS [Investigator] TIME_OBS_LOCAL [Investigator] INDEX_NUM [Investigator] SENSIBLE_HEAT_FLUX [Calculated] LATENT_HEAT_FLUX [Calculated] NET_RADIATION [Calculated] CO2_FLUX [Calculated] CRTFCN_CODE [Assigned by BORIS] REVISION_DATE [Assigned by BORIS]7.3.5 Data Range
Data range values were not computed. A value of 999 indicates that data were not available.
7.4 Sample Data Record
The following are sample data records contained
in the data files:
SITE_ID,DATE_OBS,TIME_OBS_LOCAL,INDEX_NUM,SENSIBLE_HEAT_FLUX,LATENT_HEAT_FLUX, NET_RADIATION,CO2_FLUX,CRTFCN_CODE,REVISION_DATE NSA,9-Jun-94,1630,209,54.471,85.635,187.438,0.24,CPI,29-Sep-00 NSA,9-Jun-94,1730,210,73.682,95.29,213.897,0.51,CPI,29-Sep-00 NSA,9-Jun-94,1830,211,6.382,34.779,72.857,0.01,CPI,29-Sep-00 NSA,9-Jun-94,1930,212,-1.641,6.976,-18.036,0.36,CPI,29-Sep-00Return to top of document.
8.2 Data Format(s)
The data are stored in comma separated
variable (CSV) files. There are no spaces between the fields.
9.1.1 Derivation Techniques and Algorithms
Bodies of water can potentially contribute significantly to the area-averaged heat flux at night since the air is often unstable over the water at night due to advection of cool air from land over the warm water, and, due to the weakness of the nocturnal fluxes over land. Advection of warm daytime air over cooler water may substantially suppress fluxes during the afternoon.
Two levels of complexity are considered. The simplest algorithm fits the diurnal variation of the latent and sensible heat fluxes based on aircraft data (Sun et al., 1997; Sun et al., 1998) and assume the form for heat fluxH = (10Wm-2) * cos(omega*(hr-0400)) (2)
where omega is the frequency corresponding to diurnal variations 2 pi/24 hrs. and hr is the local time. According to this formulation, the heat flux over the lake is maximum upward in the early morning (0400 local time)When the air temperature is a minimum and reaches a maximum downward in the late afternoon (1600)When the air temperature is a maximum. Even though flow over the lake is stable in the afternoon, the heat flux is comparable to the nocturnal value because of advection of strong turbulence from the heated land surface. This relationship ignores the seasonal shift of the diurnal cycle that occurs between the end of June and September.
The latent heat flux is modeled asLE = (70Wm-2) + (30Wm-2) * cos(omega*(hr-0400)) (3)
With this formulation, the latent heat flux reaches a maximum in the early morning with a value of 100 Wm-2 and a minimum of 40 Wm-2 in the late afternoon. For this simple calculation of area-averaged net radiation, the net radiation over the Water is assumed equal to the area-averaged value over the land region. The carbon dioxide flux over the Water surfaces is assumed to be zero.
Application of the bulk aerodynamic method to provide a more scientific estimate of the fluxes encounters numerous problems. The airflow and wave field would not achieve equilibrium and information on wave state would be required. Furthermore, the thermal roughness length required by similarity theory in the bulk aerodynamic approach is poorly behaved over fetches less than 5 km.The bulk aerodynamic formula is: (4)
the average of (w'*theta') = CH(z) * the average of u(z) * [theta0 - theta(z)]
where z is the observational height, theta0 is the aerodynamic temperature, and the average of u is the speed of the vector-averaged wind. The transfer coefficient is computed as:
CH(z) = [k/(ln(z/z0) - psim)] * [k/(ln(z/z0T) - psih)] (5)
where k is the von Karman constant, z0 and z0T are the roughness lengths for momentum and heat, respectively, and psim and psih are the stability functions for momentum and heat.
9.2 Data Processing Sequence
9.2.1 Processing Steps
Data were acquired from the data sources listed in Section 4.1.1. Averaged area flux data were calculated using the equations in Sections 1.5 and 9.1.1.9.2.2 Processing Changes
None given.
9.3 Calculations
9.3.1 Special Corrections/Adjustments
The net radiation measurements are adjusted according to Hodges and Smith (1997). Such adjustments are posed in terms of a linear relationship with an offset. Relationships were constructed separately for daytime and nighttime cases, here defined in terms of positive or negative net radiation. These adjustments led to minor changes in the area-averaged fluxes, partly because the sign of the difference between the corrected and uncorrected values changed between different tower sites, leading to cancellation.9.3.2 Calculated Variables
See equations in Sections 1.5 and 9.1.1.
9.4 Graphs and Plots
See figures in Section 1.5.
10.2 Quality Assessment
10.2.1 Data Validation by SourceReturn to top of document.
See Section 10.2.1 in the documentation for the data sets listed in Section 4.1.1.10.2.2 Confidence Level/Accuracy Judgment
See Section 10.2.2 in the documentation for the data sets listed in Section 4.1.1.10.2.3 Measurement Error for Parameters
See Section 10.2.3 in the documentation for the data sets listed in Section 4.1.1.10.2.4 Additional Quality Assessments
See Section 10.2.4 in the documentation for the data sets listed in Section 4.1.1.10.2.5 Data Verification by Data Center
Data were examined for general consistency and clarity.
11.2 Known Problems with the Data
See Section 11.2 in the documentation
for the data sets listed in Section 4.1.1.
11.3 Usage Guidance
See Section 11.3 in the documentation
for the data sets listed in Section 4.1.1.
11.4 Other Relevant Information
See Section 11.4 in the documentation
for the data sets listed in Section 4.1.1.
14.2 Software Access
None given.
ORNL DAAC User Services
Oak Ridge National Laboratory
(865) 241-3952
ornldaac@ornl.gov
ornl@eos.nasa.gov
15.2 Procedures for Obtaining Data
Data may be obtained through the ORNL
DAAC World Wide Web site at http://daac.ornl.gov/
[Internet Link] or users may place requests for data by telephone
or by electronic mail.
15.3 Output Products and Availability
Requested data can be provided electronically
on the ORNL DAAC's data pool site or on various media including, CD-ROMs,
8-MM tapes, or diskettes.
16.2 Film Products
None.
16.3 Other Products
Figures that accompany this documentation
are stored in GIF format.
17.2 Journal Articles and Study Reports
Chen, J., S. Leblanc, J. Cihlar, R. Desjardins and J. MacPherson, 1999:
Extending aircraft and tower-based CO2 flux measurements to
a boreal region using a Landsat TM landcover map. J. Geophys. Res., to
appear.
Desjardins, R. L., MacPherson, J. I., Mahrt, L., Schuepp, P. H., Pattey, E., Neumann, H., Baldocchi, D.,Wofsy, S., Fitzjarrald, D., McCaughey, H., and D.W. Joiner, 1997: Scaling up flux measurements for the boreal forest using aircraft-tower combinations. J. Geophys. Res., 102, 29,125-29,134.
Hodges, G. and E. Smith, 1997: Intercalibration, objective analysis, intercomparison and synthesis of BOREAS surface net radiation measurements. J. Geophys. Res., 102, 28885-28900,
Hall, F., D. Knapp and K. Huemmrich, 1997: Physically based classification and satellite mapping of biophysical characteristics in the southern boreal forest. J. Geophys. Res., 102, 29,567-29,580.
Mahrt, L., 1998: Flux sampling strategy for aircraft and tower observations. J. Atm. Oc. Tech., 15, 416-429.
Sun, J., D. Lenschow, L. Mahrt, T. Crawford, K. Davis, S. Oncley, J. I. MacPherson, Q.Wang, R. Dobosy and Desjardins, R. L.: 1997, 'Lake-Induced Atmospheric Circulations During BOREAS', J. Geophys. Res., 102, 29,155 - 29,166.
Sun, J., Desjardins, R., Mahrt, L. and MacPherson, J. I.: 1998, Transport of Carbon Dioxide,Water Vapor and Ozone by Turbulence and Local Circulations', J. Geophys. Res., 103, 25873-25,885.
Sellers, P. and F. Hall. 1994. Boreal Ecosystem-Atmosphere Study: Experiment Plan. Version 1994-3.0, NASA BOREAS Report (EXPLAN 94).
Sellers, P., F. Hall, and K.F. Huemmrich. 1996. Boreal Ecosystem-Atmosphere Study: 1994 Operations. NASA BOREAS Report (OPSDOC 94).
Sellers, P.J., 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. Bull. Am. Meteorol. Soc. 76:1549-1577.
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. 1997. Boreal Ecosystem-Atmosphere Study: 1996 Operations. NASA BOREAS Report (OPSDOC 96).
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), 28,731-28,769.
17.3 Archive/DBMS Usage Documentation
None.
ASCII - American Standard Code for Information Interchange Batoche - The study site located in the Batoche National Historic Park BFTCS - Boreal Forest Transect Case Study BOREAS - BOReal Ecosystem-Atmosphere Study BORIS - BOREAS Information System CD-ROM - Compact Disk-Read Only memory CFS - Canadian Forest Service CSV - Comma Separated Values DAAC - Distributed Active Archive Center DOY - Julian Day of Year EOS - Earth Observing System EOSDIS - EOS Data and Information System GMT - Greenwich Mean Time GSFC - Goddard Space Flight Center HTML - HyperText Markup Language IFC - Intensive Field Campaign MIX - Mixed wood NAD83 - North American Datum of 1983 NASA - National Aeronautics and Space Administration NOAA - National Oceanic and Atmospheric Administration NSA - Northern Study Area OA - Old Aspen OBS - Old Black Spruce ORNL - Oak Ridge National Laboratory PANP - Prince Albert National Park RSS - Remote Sensing Science SSA - Southern Study Area TE - Terrestrial Ecology TF - Tower Flux URL - Uniform Resource Locator UTM - Universal Transverse MercatorReturn to top of document.
Mahrt, L., D. Vickers, J. Sun, and J. H. McCaughey. 2001. BOREAS Follow-On FLX-03 Area-Averaged Flux Data for the NSA and SSA. Data set. Available on-line [http://www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.