Data used for the analysis of dominant controls on evapotranspiration from the BERMS Old Jack Pine site, Saskatchewan

https://doi.org/10.20383/101.0195

Land surface schemes can be applied to simulate evapotranspiration. This dataset contains the driving meteorological data, and various diagnostic data, from one of the Boreal Ecosystem Research and Monitoring Sites in central Saskatchewan, known as the Old Jack Pine site. In Nazarbakhsh et al. (2019, Hydrological Processes, https://doi.org/10.1002/hyp.13674 ) we used these data to drive two Canadian land surface schemes (CLASS and CLASS–CTEM). We used half–hourly values of shortwave radiation, longwave radiation, precipitation, air temperature, specific humidity, wind speed, and atmospheric pressure to drive the models. Flux tower estimates of evapotranspiration, with energy balance closure applied, were used to assess the performance of the models on daily and monthly timescales for years 2000 to 2010. We also used soil moisture (measured with Campbell Scientific CS615 probes, which measure liquid water content only) and soil temperature observations for years 2000 to 2010 to assess the models’ performance during the snowmelt and soil–thaw periods in the spring.

Nazarbakhsh, M., Ireson, A., Barr, A. (2019). Data used for the analysis of dominant controls on evapotranspiration from the BERMS Old Jack Pine site, Saskatchewan [Dataset]. Federated Research Data Repository. https://doi.org/10.20383/101.0195

Boreal Ecosystem Research and Monitoring Sites (BERMS) Old Jack Pine (OJP) site, Saskatchewan, Canada

METHODOLOGICAL INFORMATION
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This information is described in detail in the following papers:

References:

Amiro, B. D., Barr, A. G., Black, T. A., Iwashita, H., Kljun, N., McCaughey, J. H., Morgenstern, K., Murayama, S., Nesic, Z., Orchansky, A. L., & Saigusa, N. (2006). Carbon, energy and water fluxes at mature and disturbed forest sites, Saskatchewan, Canada. Agricultural and Forest Meteorology, 136, 237-251. https://doi.org/10.1016/j.agrformet.2004.11.012

Barr, A. G., van der Kamp, G., Black, T. A., McCaughey, J. H., & Nesic, Z. (2012). Energy balance closure at the BERMS flux towers in relation to the water balance of the White Gull Creek watershed 1999-2009. Agricultural and Forest Meteorology, 153, 3-13. https://doi.org/10.1016/j.agrformet.2011.05.017

Cuenca, R. H., Stangel, D. E., & Kelly, S. F. (1997). Soil water balance in a boreal forest. Geophysical Research, 102(D24), 29355-29365. https://doi.org/10.1029/97jd02312

Hejazi, A., & Woodbury, A. D. (2011). Evaluation of land surface scheme SABAE-HW in simulating snow depth, soil temperature and soil moisture within the BOREAS site, Saskatchewan. Atmosphere̶Ocean, 49:4, 408-420, https://doi.org/10.1080/07055900.2011.587238

1. Description of methods used for collection/generation of data:

Air temperature and precipitation were measured at BERMS Old Jack Pine site using temperature/humidity probes (Vaisala model HMP45C) mounted in radiation shield above the canopy and an accumulating gauge (Belfort model 3000), respectively.
Incoming shortwave and longwave radiation were measured at BERMS Old Jack Pine site using a pyranometer (Kipp and Zonen model CM11) and a pyrgeometer (Eppley model PIR). Wind speed and direction were measured at BERMS Old Jack Pine site using a RMY Propeller Anemometer Model 05103.
Barometric pressure was measured using a Setra Model 270 Barometer. Specific humidity was derived from the measurements of air temperature, relative humidity and barometric pressure.
Soil temperature was measured at BERMS Old Jack Pine site using Cu-Co thermocouple sensor at 2, 5, 10, 20, 50 and 100 cm soil depth (Hejazi and Woodbury, 2011)(See the reference above).
The soil volumetric water content was measured at BERMS Old Jack Pine site using soil moisture reflectometers (Campbell Scientific CS615 probes) at 0-15, 15-30, 30-60, 60-90, 90-120 and 120-150 cm depth.
Evapotranspiration was measured at BERMS Old Jack Pine site using the eddy-covariance method, with an energy balance closure adjustment applied. For more detailed explanation about the collection of data, see the reference above (Barr et al. 2012).

2. Methods for processing the data:

Gaps in evapotranspiration data were filled using the Fluxnet-Canada gap-filling method as described by Amiro et al. (2006) (the reference above).

3. Instrument- or software-specific information needed to interpret the data:

The evapotranspiration data were adjusted to force surface-energy-balance closure using an energy-closure fraction of 0.85, i.e. Adjusted ET = Measured ET / 0.85. This was an objective adjustment based on Barr et al. (2012) (above).

4. Standards and calibration information, if appropriate: n/a

5. Environmental/experimental conditions: n/a

6. Describe any quality-assurance procedures performed on the data:

"Three factors reduced the uncertainties including the analysis of multiple years of data from multiple sites; the tendency of change in soil water storage to become small when averaged over many years; and the careful design of the measurement systems to eliminate systematic errors.
The design features included: use of high-quality radiometers with frequent calibration and no signs of calibration drift; careful measurement of the surface energy storage fluxes; use of closed-path, short-tube eddy-covariance systems with high flow rates through temperature-controlled gas analyzers;
careful processing and quality assurance of the eddy-covariance data; use of accumulating precipitation gauges located in small forest clearings in near-optimal conditions to minimize undercatch; complete measurements of soil water storage including root-zone water content and water table depth; and frequent maintenance of the streamflow gauge.
The sites in this study were all continental, with level topography and uniform fetch; all had high-quality measurements of surface available energy; and all used standardized eddy-covariance instrumentation and data-processing software." (Barr et al. 2012).
For more detailed explanation about quality-assurance procedures performed on the data, see the reference above (Barr et al. 2012).

Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

Data is available for download from https://doi.org/10.20383/101.0195