tutorial-07: glue analysis laura dobor, péter ittzés, dóra ittzés, ferenc horváth & zoltán...
TRANSCRIPT
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
BOX WROTE THAT „Essentially, all models are wrong,
but some are useful"
MODULE X:Understanding basics of GLUE Analysis
1) Purpose and main features of GLUE = Generalized Likelihood Uncertainty Estimation
AIM: to estimate parameter values
NEEDS: based on observation data & Monte Carlo Experiment
METHOD: 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
2) Randomized parameters, output settings (MCE) + + Observational dataset >>> GLUE options
GLUE needs careful preparation!
A) Monte Carlo Experiment:-- randomize the parameters which you want to calibrate -- ask for the outputs wherefor you have observation
b) 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!
MODULE X:Guess a riddle!
-- We defined 3 different epc files with differences in a few parameters give invented 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
Canopy average specific leaf area 49 49 32Leaf N in Rubisco 0.21 0.12 0.21
HA
RM
ON
Y
NIT
RO
GE
N
LEA
FA
RE
A
Differencies in the defined epc-s
Already exist Monte Carlo Experiments based onthe 3 different epc…
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!
How to run GLUE?GO TO PORTAL:
http://workshop.at.biovel.euLOG IN! GO TO ECOSYSTEM MODELING!
SELECT GLUE WORKFLOW TO RUN…
GIVE A NAME…START RUN……WAIT FOR THE INTERACTION PAGE…
SET YOUR RUN ON THE INTERACTION PAGE…
GIVE A NAME TO THE RUN…
Biome-BGC MuSo 2.2
TEST DEMO HHS (HU) [855]
SET YOUR RUN…AIR, NINE OR HUMUS
HARMONY, NITROGEN OR LEAFAREA
TEST DEMO HHS MCE FIVEPARAMS 10.000 ….HARMONY [1145]
TEST DEMO Daily observation data 2001-2002 – AIR [1164]
CHECK THE STATUS OF YOUR RUN AT PROJECT DATABASE…GET THE RESULTS
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
EPC filesHARMONYNITROGENLEAFAREA
ObservationsAIR
HUMUSNINE
?
Canopy average specific leaf area 49 49 32Leaf N in Rubisco 0.21 0.12 0.21
HA
RM
ON
Y
NIT
RO
GE
N
LEA
FA
RE
A
Differencies in the defined epc-s
Match the pairs!
Answers…
HUMUS observation compared to MCE
0.35
0.355
0.36
0.365
0.37
0.375
0.38
0.385
0.39
0 0.1 0.2 0.3 0.40.35
0.355
0.36
0.365
0.37
0.375
0.38
0.385
0.39
0 50 100
Canopy average specific leaf areaLeaf N in Rubisco
Find max Likelihood…Canopy average specific leaf area 49 49 32Leaf N in Rubisco 0.21 0.12 0.21
HARMONY
Like
lihoo
d
Like
lihoo
d
0.345
0.35
0.355
0.36
0.365
0.37
0.375
0.38
0.385
0.39
0 0.1 0.2 0.3 0.40.345
0.35
0.355
0.36
0.365
0.37
0.375
0.38
0.385
0.39
0 50 100
AIR observation compared to MCE
Canopy average specific leaf areaLeaf N in Rubisco
Find max Likelihood…Canopy average specific leaf area 49 49 32Leaf N in Rubisco 0.21 0.12 0.21
LEAFAREA
Like
lihoo
d
Like
lihoo
d
0.345
0.35
0.355
0.36
0.365
0.37
0.375
0.38
0.385
0.39
0 0.1 0.2 0.3 0.4
0.345
0.35
0.355
0.36
0.365
0.37
0.375
0.38
0.385
0.39
0 50 100
NINE observation compared to MCE
Canopy average specific leaf areaLeaf N in Rubisco
Find max Likelihood…Canopy average specific leaf area 49 49 32Leaf N in Rubisco 0.21 0.12 0.21
NITROGEN
Like
lihoo
d
Like
lihoo
d
EPC filesHARMONYNITROGENLEAFAREA
ObservationsAIR
HUMUSNINE
Canopy average specific leaf area 49 49 32Leaf N in Rubisco 0.21 0.12 0.21
HA
RM
ON
Y
NIT
RO
GE
N
LEA
FA
RE
A
Differencies in the defined epc-s
Match the pairs!
Thank you for your attention!