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GPP(GEE),RE(ER) and comparisons

This study presents an in-depth comparison of 15 methodologies for estimating Gross Primary Production (GPP) and Respiration (RE) through gap-filling techniques. Data from 12 site-years and 51 scenarios are utilized for analysis. Preliminary findings indicate that 13 out of the 15 methods yield results for GPP and RE, with diagnostics including mean, variance, and box plots across methods. Future actions include refining the methodology by incorporating synthetic noisy data and validating results against independent datasets. Aiming for a manuscript submission after comprehensive evaluations.

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GPP(GEE),RE(ER) and comparisons

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  1. GPP(GEE),RE(ER) and comparisons Oh My! Ankur Desai, et al. The Gap Filling Society Jena, 20 Sept 2006

  2. What we’re doing (status quo) • Using same dataset from NEE gap filling (12 site-years, 51 scenarios/site) to comparing GPP & RE across methods • 13 of 15 methods produce GPP & RE • 9 of these analyzed so far • With variants, currently at 19 analyzed • Unlike NEE, no benchmark • However, BETHY model is part of group • Can use BETHY as benchmark as a 1st try • Perhaps synthetic noisy data would help • Questions on how to fill + decompose NEE

  3. What we’ve done so far • To date, all datasets have been processed and put in common binary format • Daily and annual sums of GPP & RE computed • Mean and variance across 51 replicates and across methods computed • Diagnostic plots made • Box plots look at GPP/RE across methods (letters) , replicates (gray bars), mean and st.dev (+) across methods and range (box) • Colors delineate method type

  4. Who’s doing what

  5. What we’ve found so far

  6. What we’ve found so far

  7. What’s next (action items) • Get all data for methods that want to be part of comparison • Skipping analysis of il1_2002, it3_2001 • Only testing 10 Mixed gaps only + r0 (no artificial gaps) • Fill and decompose as you would when gapfilling and publishing GPP & RE for your sites – due end of October for inclusion • Run other benchmarks and tests • Run GPP and RE analysis with synthetic noisy daya • Jens K. to give Dave H. BETHY data (all sites), Dave H. to corrupt (add noise), Antje to gapify (10 mixed scenarios w/ 35% missing + 0% missing) - next 3-4 mos • Run “corrupt” data through GPP/RE decomp. methods – by Feb • Produce diurnal plots by season and scatter plots • Perform ANOVA of GPP and RE for site x method • Compare to independent data (chamber, inventory, etc…) • Share data/results with group – as acquired/analyzed - Ankur D. • Write 1st draft manuscript – Dec-Jan (Ankur D.) • Discuss – Ankur D. to create wiki this fall • Submit sometime afterward (interest in rapid publication, co-publication with gapfilling paper)

  8. Manuscript outline • Title • GPP and RE rock • Abstract • See below • Introduction • Why?, Hypotheses, Prior work • Methods • Decomposition, methods, sites, comparison, statistics, synthetic data analysis, • Results • Pretty pictures that corroborate or refute hypotheses • Discussion • What does it all mean, can we trust GPP & RE from EC data and with what confidence, what does synthetic analysis imply • Conclusion • We told you so

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