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The CarboeuropeIP Ecosystem Component Database: data processing and availability

The CarboeuropeIP Ecosystem Component Database: data processing and availability. Dario Papale, Markus Reichstein. Database. Typically, the “bilateral meetings” talk…. Why do we need a database?. Modelers. Flux people. Knowledge in Modeling and data synthesis. Knowledge in Eddy Covariance.

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The CarboeuropeIP Ecosystem Component Database: data processing and availability

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  1. The CarboeuropeIP Ecosystem Component Database: data processing and availability Dario Papale, Markus Reichstein

  2. Database Typically, the “bilateral meetings” talk…. Why do we need a database?

  3. Modelers Flux people Knowledge in Modeling and data synthesis Knowledge in Eddy Covariance

  4. What is it needed? • Data, provided by the PIs and shared with the scientific community • Data have to be with good quality (the user are not able to understand this looking to the dataset…) • Data have to be in the same format • Data have to be “ready to be used”

  5. http://gaia.agraria.unitus.it/database

  6. Info used in the email to the PIs

  7. And also the list of downloads from your site…

  8. Data quality centralized checks Why do we need to correct the data if the PIs correctly apply all the quality checks? How many PIs are applying these tests/corrections correctly? How many PIs are reprocessing old data with new methods? and…..

  9. Datasets available on the database Different levels of products and different versions Level 0.x Conversion (Site) Two steps quality checks Level 1.x QC I (Site & DB) Level 2.x QC II (DB)(semi-automatic) Level 3.x GF/FP/aggregation (DB)(automatic) Level 4.x

  10. 9 bits QC flag

  11. QC II for level 3 products Rg vs Potential radiation Rg vs PPFD ustar vs wind speed • Fluxes • Marginal or isolated points • Spikes • Low variability periods • Storage correction • With the storage measured using a profile system • Using the top-of-tower CO2 conc. u* filtering

  12. Global radiation vs PPFD

  13. Spikes detection method NB: these are low frequency spikes, different from the raw data spikes!!!!

  14. Standardized ustar filtering

  15. Ustar threshold selection method M x selected as threshold if flux(x) >= M x 0.99 x This is done for 6 different temperature classes (only if no relation between T and u* are found) and for 4 season. Seasonal ustar is calculated as median on the 6 thresholds, for annual u* the maximum seasonal value is taken

  16. ITRo1 2000

  17. BEVie 2002

  18. NLLoo 1998 – storage with discrete approach

  19. NLLoo 1998 – storage with profile

  20. ITLav 2002

  21. … then we fill gaps with two methods (ANN and MDS) and calculate GPP and TER ….. BEVie 2002

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