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Hewlley Acioli  hewlley@vicosa.ufv.br Marcos Heil Costa  mhcosta@ufv.br - PowerPoint PPT Presentation


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NET ECOSYSTEM EXCHANGE (NEE) SENSITIVITY TO DIFFERENT FILTERS AT LBA_MIP FOREST SITE. Hewlley Acioli  hewlley@vicosa.ufv.br Marcos Heil Costa  mhcosta@ufv.br Luis Gustavo G de Gonçalves  luis.g.degoncalves@nasa.gov Bradley J. Christoffersen  bchristo@email.arizona.edu

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slide1

NET ECOSYSTEM EXCHANGE (NEE) SENSITIVITY TO DIFFERENT FILTERS AT LBA_MIP FOREST SITE

Hewlley Acioli  hewlley@vicosa.ufv.br

Marcos Heil Costa  mhcosta@ufv.br

Luis Gustavo G de Gonçalves  luis.g.degoncalves@nasa.gov

Bradley J. Christoffersen bchristo@email.arizona.edu

Ian Baker  baker@atmos.colostate.edu

Ben Poulter bem.poulter@pik-potsdam.de

Natalia Restrepo ncoupe@email.arizona.edu

Scott R. Saleska saleska@email.arizona.edu

Manaus

November, 2008

slide2

INTRODUCTION

  • Net ecosystem exchange (NEE)
  •  Is the result of the difference between two large fluxes
  • PLANT PHOTOSYNTHESIS AND RESPIRATION
  • Can be quantified at different time scales
  • Eddy Covariance Technique (EC)
  • Is based on the high-frequency measurement of the vertical wind speed and of the CO2 above plant canopies, coupled with measurements of CO2 storage below the measurement point using slow response infrared gas analyzers (Aubinet et al., 2000).
slide3

Eddy Covariance Technique (EC)  SHORTCOMINGS!

    • During stable conditions at night
      • Because non-turbulent transport processes are not taken into account by the EC system
  • The night flux error acts as a selective systematic error (Moncrieff et al., 1996)
  • Its impact on the CO2 exchange and on the estimation of the carbon sequestration by the forest
  • A small nighttime bias error of the 1 μmol m-2 s-1, aggregated for 12 h nights over one year is equivalent to 189 g C m-2 year-1 (Aubinet et al.,2005)
slide4

A number of screening criteria to filter the data under these conditions have been suggested!

These criteria essentially consist of replacing data from nights with low turbulence with those measured in nights with similar characteristics, but enough mixing.

  • The friction velocity (u*)
  • Nightly average of NEE (umean)
  • The standard-deviation of the vertical velocity fluctuations (σw)
slide5

OBJECTIVE:

  • To evaluate the effect of different filtering procedures on the performance of LBA_MIP models
  • Two filtering criteria used in these analyses
  • The friction velocity (u*) filter:
    • This is a measure of turbulent mixing intensity
    • The u* correction neglects data from nights for which the turbulence velocity scale is lower than a given threshold.
  • FLAG filter
    • The FLAG filter doesn’t use the gap-filled data
slide6

 DATA TREATMENT

    • Gap-filled data (FLAG)
    • Turbulence threshold (u*0 = 0.1 m/s)
    • Turbulence threshold (u*0 = 0.2 m/s)
    • FLAG and u*0 = 0.1 m/s
    • FLAG and u*0 = 0.2 m/s
slide7

 EXPERIMENTAL SITE

  • Flona Tapajós km 67
slide29

SUMMARY

AND CONCLUSIONS

slide30

Simulated NEE from km 67 site was sensitive to the FLAG and u* filters

  • For the IBIS, CLM3.5 and BGC models from km 67 the best results were obtained when the FLAG and u* filters are not used
  • For the SiB3 the FLAG & u* = 0.1 filter produced a better result than not using any filter.
  • The same procedure will be performed for others LBA_MIP sites
  • Other potential filtering techniques may be used in the future (umean, σw …)