DATASET: Ivotuk Climate and Flux Data for 1998

PI: Jason Beringer

DATA COLLECTION AND PROCESSING:
Surface energy and trace gas exchange measurements were made at each site using the eddy covariance technique. The MAT site was operated continuously over the growing season whilst the remaining sites were characterized by a single tower that was moved from site to site. The MAT site is therefore used as a reference.

Tower-based microclimatic and eddy-covariance measurements were used to characterize the radiation balance and energy budget above different tundra types. Two towers were developed for this measurement campaign. Simultaneous measurements of energy and trace gas exchanges were made at both the MAT over the entire growing season using the eddy covariance technique (Eugster et al. 1997). Measurements at the other sites were measured consecutively but in parallel to the MAT site.

We used 3m towers at all sites. Radiation measurements were made as close as practical to the top of the towers to minimize the potential of shading from above and to maximize the surface area within the effective sensor footprint (Schmid 1997). Eddy-covariance measurements were made at varying heights above the vegetation.

Three dimensional wind velocities were measured using a 3-D ultrasonic anemometer (Gill Solent, horizontally symmetric) and were co-ordinate rotated. Turbulent fluctuations of CO2 and H2O were measured using a LICOR 6262 closed path infrared gas analyser. A 3mm internal diameter "Bev-A-Line" intake tube was used for the gas analyzer with an aspiration rate of approximately 7 L.min-1 that ensured turbulent flow in the sample line, 1.5m of externally insulated copper tubing was placed inline to minimize temperature-induced density fluctuations (Leuning & Judd 1996). The observations were logged at 10Hz to a nearby laptop PC.

The w'T' cospectra followed the idealized cospectra and the w'CO2' and w'H2O' were spectrally corrected following (Eugster and Senn 1995). Spectral correction factors for water vapour were less than 1.4 during daylight hours. The energy balance closure was generally less than 20% of Rn during the daylight hours indicating satisfactory measurement techniques and confidence in the measured fluxes.

Climate sensors were measured every 30-seconds and 10-minute averages were recorded on a data-logger (Campbell Scientific Inc., CR10X). Incoming and reflected shortwave as well as incoming and emitted long-wave radiation were measured using a pair of pyranometers (Eppley Inc., model PSP) and a pair of pyrgeometers (Eppley Inc., model PIR) respectively. An independent estimate of net radiation above each surface was made using a Frischen type net radiometer (REBS, model Q7.1) with a wind-speed-dependant dome cooling correction applied to the results (REBS Q7.1 Manual).

Profiles of air temperature and water vapor content above and below the level of the sonic anemometer were measured using temperature/relative humidity probes (Vaisala, model HMP45C). Wind speed at the radiometer height was measured using a cup anemometer (R.M Young, 03101). Ground heat flux was estimated via the combination method (Oke 1987) using heat flux plates (REBS, HFT3) and soil temperature measurements (REBS, PRT) at four representative locations. Ground heat flux for each tower site was estimated using the area-weighted average of ground heat fluxes measured in each of the representative microsite types (e.g., lichen-dominated vs. moss-dominated microsites).

DATA FORMAT:
Data are divided into two categories (either climate or flux). There are 4 sites I1-I4. Hence there are 8 filenames
I1_flux
I1_climate
I2_flux
I2_climate
I3_flux
I3_climate
I4_flux
I4_climate

These files are saved in two formats *.xls being an Excel4 worksheet and *.txt being a comma delineated text file.

The files contain one or more of the following parameters and the parameter names are given at the top of each column. The following table gives the parameter definitions.

Note that in each flux file there is a VALD column which is a flag to indicate good quality data. Data with a 1 is identified as good data.