DOI QR코드

DOI QR Code

Quality Control and Characteristic of Eddy Covariance Data in the Region of Nakdong River

낙동강 유역에서 관측된 에디 공분산 자료의 품질 관리 및 플럭스 특성

  • Lee, Young-Hee (Department of Astronomy and Atmospheric Sciences, Kyungpook National University) ;
  • Lee, Byoungju (Applied Meteorological Research Lab., National Institute of Meteorological Research) ;
  • Kahng, Keumah (Applied Meteorological Research Lab., National Institute of Meteorological Research) ;
  • Kim, Soo-Jin (Department of Astronomy and Atmospheric Sciences, Kyungpook National University) ;
  • Hong, Seon-Ok (Department of Astronomy and Atmospheric Sciences, Kyungpook National University)
  • 이영희 (경북대학교천문대기과학과) ;
  • 이병주 (국립기상연구소응용기상연구과) ;
  • 강금아 (국립기상연구소응용기상연구과) ;
  • 김수진 (경북대학교천문대기과학과) ;
  • 홍선옥 (경북대학교천문대기과학과)
  • Received : 2013.04.08
  • Accepted : 2013.07.16
  • Published : 2013.09.30

Abstract

We performed comprehensive quality control for eddy-covariance measurements from 3 farmland sites and 1 industrial site adjacent to Nakdong river. The quality control program is based on Foken and Wichura (1996) and Vicker and Mahrt (1997) and we added criteria for trend and standard deviation for scalar variables and modified criteria for non-stationarity condition of Foken and Wichura (1996) to consider random error of fluxes. The classification of data quality is designed for the raw data and the processed flux data, separately. Use of added criteria efficiently reduces the number of outlier for water vapor and $CO_2$ fluxes and use of modified criteria for non-stationarity reduces the number of outlier for scalar fluxes and increases the number of data with accepted quality for further work. Energy balance ratio is higher in farmlands than industrial site, which is due to neglect of heat storage term in industrial site. Among farmland sites, C4 site shows higher energy balance ratio than other sites. This is due to more homogeneous surface of C4 site than other farmland sites. However, energy balance ratio is very low or even negative at night. Mismatch between the flux footprint and the other energy component footprint over the heterogeneous surface is main cause for energy imbalance at night. Other possible causes are also discussed.

Keywords

References

  1. Arya, S. P., 2001: Introduction to micrometeorology. AcademicPress, 420 pp.
  2. Billesbach, D. P., 2011: Estimating uncertainties in individual eddy covariance flux measurements: A comparison of methods and a proposed new method. Agric. Forest Meteor., 151, 394-405. https://doi.org/10.1016/j.agrformet.2010.12.001
  3. Finkelstein, P. L., and P. F. Sims, 2001: Sampling error in eddy correlation flux measurements. J. Geophys. Res., D4 106, 3503-3509.
  4. Foken, Th., and B. Wichura, 1996: Tools for quality assessment of surface-based flux measurements. Agric. Forest Meteor., 78, 83-105. https://doi.org/10.1016/0168-1923(95)02248-1
  5. Hollinger, D. Y., and A. D. Richardson, 2005: Uncertainty in eddy covariance measurements and its application to physiological models. Tree Physol., 25, 873-885. https://doi.org/10.1093/treephys/25.7.873
  6. Hong, J., and J. Kim, 2002: On processing raw data from micrometeorological field experiments. Korean J. Agric. Forest Meteor., 4, 119-126.
  7. Hong, J., H. Kwon, J.-H. Lim, Y.-H. Byun, J. Lee, and J. Kim, 2009: Standardization of KoFlux eddy-covariance data processing. Korean J. Agric. Forest Meteor., 11, 19-26. https://doi.org/10.5532/KJAFM.2009.11.1.019
  8. Kaimal, J. C., and J. J. Finnigan, 1994: Atmospheric Boundary layer flows. Oxford, 289 pp.
  9. Lee, X., W. Massman, and B. Law, 2004: Handbook of Micrometeorology. Kluwer Academic Publishers, 250 pp.
  10. Lim, H.-J., and Y.-H. Lee, 2008: Processing and quality control of flux data at Gwangneung forest. Korean J. Agric. Forest Meteor., 10, 82-93. https://doi.org/10.5532/KJAFM.2008.10.3.082
  11. Mahrt, L., 1998: Flux sampling errors for aircraft and towers. J. Atmos. Ocean. Technol., 15, 416-429. https://doi.org/10.1175/1520-0426(1998)015<0416:FSEFAA>2.0.CO;2
  12. Mann, L., and D. H. Lenschow, 1994: Errors in airborne flux measurements. J. Geophys. Res., 99, 14519- 14526. https://doi.org/10.1029/94JD00737
  13. Mauder, M., T. Foken, R. Clement, J. A. Elbers, W. Eugster, T. Grunwald, B. Heusinkveld, and O. Kolle, 2008: Quality control of CarbonEurope flux data - Part 2: Inter-comparison of eddy-covariance software. Biosci., 5, 451-462.
  14. Nordbo, A., L. Jarvi, and T. Vesala, 2012: Revised eddy covariance flux calculation methodologies-effect on urban energy balance. Tellus B, 64, 18184. https://doi.org/10.3402/tellusb.v64i0.18184
  15. Panin, G. N., G. Tetzlaff, and A. Raabe, 1998: Inhomogeneity of the land surface and problems in the parameterization of surface fluxes in natural conditions. Theor. Appl. Climatol., 60, 163-178. https://doi.org/10.1007/s007040050041
  16. Papale, D., M. Reichstein, M. Aubinet, E. Canfora, C. Bernhofer, W. Kutsch, B. Longdoz, S. Rambal, R. Valentini, T. Vesala, and D. Yakir, 2006: Towards a standardized processing of net ecosystem exchange measured with eddy covariance technique: algorithms and uncertainty estimation. Biosci., 3, 571-583.
  17. Schmid, H. P., 1994: Source areas for scalars and scalar fluxes. Bound.-Layer Meteor., 67, 293-318. https://doi.org/10.1007/BF00713146
  18. Stull, R. B., 1988: An introduction to boundary layer meteorology. Kluwer Academic Publishers, 670 pp.
  19. Vicker, D., and L. Mahrt, 1997: Quality control and flux sampling problems for tower and aircraft data. J. Atmos. Oceanic Tech., 14, 512-526. https://doi.org/10.1175/1520-0426(1997)014<0512:QCAFSP>2.0.CO;2
  20. 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. Meteor. Soc., 106, 85-100. https://doi.org/10.1002/qj.49710644707
  21. Wilson, K., and Coauthors, 2002: Energy balance closure at FLUXNET sites. Agric. Forest Meteor., 113, 223-243. https://doi.org/10.1016/S0168-1923(02)00109-0

Cited by

  1. Analysis of local wind induced by surface heterogeneity and sloping terrain near Nakdong river vol.51, pp.3, 2015, https://doi.org/10.1007/s13143-015-0075-4
  2. Uncertainty Analysis of the Eddy-Covariance Turbulent Fluxes Measured over a Heterogeneous Urban Area: A Coordinate Tilt Impact vol.26, pp.3, 2016, https://doi.org/10.14191/Atmos.2016.26.3.473
  3. Estimation of the Random Error of Eddy Covariance Data from Two Towers during Daytime vol.26, pp.3, 2016, https://doi.org/10.14191/Atmos.2016.26.3.483
  4. Analysis of surface energy balance closure over heterogeneous surfaces vol.50, pp.S1, 2014, https://doi.org/10.1007/s13143-014-0045-2
  5. Effects of Different Averaging Operators on the Urban Turbulent Fluxes vol.24, pp.2, 2014, https://doi.org/10.14191/Atmos.2014.24.2.197