Seminar: Martin Jung
- Date: Sep 29, 2022
- Time: 02:00 PM - 03:00 PM (Local Time Germany)
- Speaker: Martin Jung
- Reichstein Department
- Location: Max-Planck-Institut für Biogeochemie
- Room: Hörsaal (C0.001)
- Host: tbd
Flux tower data have revolutionized our ability to quantify, understand, and model ecosystem responses to environmental conditions across diurnal to decadal time-scales. The availability of global collections of synthesized flux tower data has accelerated scientific progress beyond the eddy covariance community facilitating integrations with satellite remote sensing and ecosystem modelling. Despite continued maturation of the measurement techniques and data processing over the last decades there are remaining data quality issues in global FLUXNET data that pose challenges for users, in particular those that are not flux tower data experts.
Here we present a complementary flux tower data quality control approach based on multiple indications of inconsistency among variables along with a methodology to detect discontinuities in time series. The final results are for NEE, GPP, TER, LE, H, SW_IN, NETRAD, PPFD, TA, VPD and consist of: (1) Boolean flags for daily data values, (2) Boolean flags for entire site variables, (3) flags at time stamps that mark large discontinuities in the time series. The methodology is based on transparent principles, fully automated and applicable across heterogeneous data conditions, is flexible for customizing and improving, and allows for varying the desired strictness of the quality control. Applying the quality control approach to the FLUXNET 2015 dataset reveals (1) frequent and systematic rejections for GPP and TER under dry and hot conditions due to flux partitioning issues that limit our capability to better understanding drought and rain pulse responses, (2) comparatively frequent rejections for radiation variables that are crucial for correctly interpreting and modelling ecosystem fluxes, (3) frequently detected discontinuities in long time series of LE, NEE, and radiation variables that raise caution flags for studying interannual variations and trends.We hope that our quality control approach facilitates a better use of flux tower data across communities, and ultimately leads to better data in the long-term by accelerating the feedback loop between PIs and centralized processing facilities.
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