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TUTORIAL-07: GLUE Analysis

TUTORIAL-07: GLUE Analysis. Laura Dobor, Péter Ittzés, Dóra Ittzés, Ferenc Horváth & Zoltán Barcza Training WS for Ecosystem Modelling studies Budapest, 29-30 of May, 2014. Box wrote that „ E ssentially, all models are wrong, but some are useful".

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TUTORIAL-07: GLUE Analysis

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  1. TUTORIAL-07:GLUE Analysis Laura Dobor, Péter Ittzés, Dóra Ittzés, Ferenc Horváth & Zoltán Barcza Training WS for Ecosystem Modelling studiesBudapest, 29-30 of May, 2014

  2. Box wrote that „Essentially, all models are wrong, but some are useful"

  3. MODULE X:Understanding basics of GLUE Analysis1) Purpose and main features of GLUE = Generalized Likelihood Uncertainty EstimationAIM: to estimate parameter valuesNEEDS: based on observation data & Monte Carlo ExperimentMETHOD: compare the obs to different model results (based on different parameter sets) Find out which parameter set gives the best results to our observations?How to measure the goodness of the outputs? misfit calculation (root mean square error)  likelihood calculationGreater LH value refers to better parameter set

  4. 2) Randomized parameters, output settings (MCE) + + Observational dataset >>> GLUE optionsGLUE needs careful preparation!A) Monte Carlo Experiment:-- randomize the parameters which you want to calibrate -- ask for the outputs wherefor you have observationb) Observation data:-- match your observation to one of the MuSo outputs (look up for the variable short name and code at the output variables)-- prepare your file in csv format and upload it to the database Run GLUE workflow at the portal!

  5. MODULE X:Guess a riddle!-- We defined 3 different epc files with differences in a few parameters  giveinvented names to them (HARMONY, LEAFAREA, NITROGEN)-- We run carbon simulations and get the outputs-- We defined these unreal-data as observation datasets in the project database  give invented names to them (HUMUS, AIR, NINE)The question is: Which observation comes from which ecophysiological parametrization?KEY: Use the GLUE analysis!Group work:Creat 3 groups, each select one obs dataset

  6. HARMONY NITROGEN LEAFAREA Differencies in the defined epc-s Canopy average specific leaf area 49 49 32 Leaf N in Rubisco 0.21 0.12 0.21

  7. Already exist Monte Carlo Experiments based on the 3 different epc…

  8. The question is: Which observation comes from which ecophysiological parametrization?Exercise:1) Choose one TEST DEMO Daily Observation dataset (i.e. NINE)2) Run a GLUE workflow at the portal compare your obs data to the different MCEresults (i.e. NINE X LEAFAREA; NINE X HARMONY …)3) Download (from database) and check the results in Excel!4) Draw GLUE plots and try to answer the question!

  9. How to run GLUE?GO TO PORTAL: http://workshop.at.biovel.euLOG IN! GO TO ECOSYSTEM MODELING!

  10. SELECT GLUE WORKFLOW TO RUN…

  11. GIVE A NAME…START RUN……WAIT FOR THE INTERACTION PAGE…

  12. SET YOUR RUN ON THE INTERACTION PAGE… GIVE A NAME TO THE RUN… Biome-BGC MuSo 2.2 TEST DEMO HHS (HU) [855]

  13. HARMONY, NITROGEN OR LEAFAREA SET YOUR RUN… AIR, NINE OR HUMUS TEST DEMO HHS MCE FIVEPARAMS 10.000 ….HARMONY [1145] TEST DEMO Daily observation data 2001-2002 – AIR [1164]

  14. CHECK THE STATUS OF YOUR RUN AT PROJECT DATABASE…GET THE RESULTS

  15. GLUE RESULTS:2 FILESLOOK THE randinputs_likelihoods.csvEvery line refers to one parameter set. Last column is the likelihood value. plot likelihood vs parameters one-by-one

  16. EPC files HARMONY NITROGEN LEAFAREA Match the pairs! Observations AIR HUMUS NINE  ? HARMONY NITROGEN LEAFAREA Differencies in the defined epc-s Canopy average specific leaf area 49 49 32 Leaf N in Rubisco 0.21 0.12 0.21

  17. Answers…

  18. HUMUS observation compared to MCE Leaf N in Rubisco Canopy average specific leaf area Likelihood Likelihood HARMONY Find max Likelihood… Canopy average specific leaf area 49 49 32 Leaf N in Rubisco 0.21 0.12 0.21

  19. AIR observation compared to MCE Leaf N in Rubisco Canopy average specific leaf area Likelihood Likelihood LEAFAREA Find max Likelihood… Canopy average specific leaf area 49 49 32 Leaf N in Rubisco 0.21 0.12 0.21

  20. NINE observation compared to MCE Leaf N in Rubisco Canopy average specific leaf area Likelihood Likelihood NITROGEN Find max Likelihood… Canopy average specific leaf area 49 49 32 Leaf N in Rubisco 0.21 0.12 0.21

  21. EPC files HARMONY NITROGEN LEAFAREA Match the pairs! Observations AIR HUMUS NINE HARMONY NITROGEN LEAFAREA Differencies in the defined epc-s Canopy average specific leaf area 49 49 32 Leaf N in Rubisco 0.21 0.12 0.21

  22. Thank you for your attention!

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