BiomeBGC GLUE 1.3
Created: 20141002 10:27:29
Last updated: 20141009 05:30:02
BiomeBGC is working with a lots of ‘a priori’ unknown and hard to obtain model parameters. Therefore the parameterization is a critical step of using the model. Parameteres can be estimated using inverse calibration techniques based on measurement data, which means that the model is being calibrated. Measurement data have to be collected with respect to the model in order to compare them. Comparison is based on misfit measure (e.g. a sort of likelihood value), which is the function of the difference between observed and modelled data. It is based on Bayesian calibration with Monte Carlo search. Each parameter is varied randomly within their ‘a priori’ range and the model is run several times using variable model parameters. Then the ‘a priori’ distribution is updated with model information (distribution of the likelihood function) to define ‘a posteriori’ density function. From the maximum of the ‘a posteriori’ density function optimal parameter values can be calculated and approved.
GLUE requires a prior execution of a BiomeBGC Monte Carlo Experiment (MCE), that performs an independent parameter variation within ‘a priori’ parameter ranges. Parameters, range of parameter values, output variables and number of randomized repetition has to be set in BiomeBGC MCE workflow, that runs offline because of the time consuming nature of MCE jobs (usually it takes several days on, for example the EDGeS@home desktop grid). Then one or several GLUE analysis can be launched based on the results of BiomeBGC MCE completed before.
The BiomeBGC Projects Database & Management System was developed to easy prepare, manage and share all of the above mentioned datasets (files), investigations and provide interaction with Taverna workflows. Learn more about BBGCDB at http://ecos.okologia.mta.hu/bbgcdb/.
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Authors (1)
Dora KRASSER, Peter ITTZES, Zoltan BARCZA and Ferenc HORVATH 
Titles (1)
Descriptions (1)
BiomeBGC is working with a lots of ‘a priori’ unknown and hard to obtain model parameters. Therefore the parameterization is a critical step of using the model. Parameteres can be estimated using inverse calibration techniques based on measurement data, which means that the model is being calibrated. Measurement data have to be collected with respect to the model in order to compare them. Comparison is based on misfit measure (e.g. a sort of likelihood value), which is the function of the difference between observed and modelled data. It is based on Bayesian calibration with Monte Carlo search. Each parameter is varied randomly within their ‘a priori’ range and the model is run several times using variable model parameters. Then the ‘a priori’ distribution is updated with model information (distribution of the likelihood function) to define ‘a posteriori’ density function. From the maximum of the ‘a posteriori’ density function optimal parameter values can be calculated and approved.
GLUE requires a prior execution of a BiomeBGC Monte Carlo Experiment (MCE), that performs an independent parameter variation within ‘a priori’ parameter ranges. Parameters, range of parameter values, output variables and number of randomized repetition has to be set in BiomeBGC MCE workflow, that runs offline because of the time consuming nature of MCE jobs (usually it takes several days on, for example the EDGeS@home desktop grid). Then one or several GLUE analysis can be launched based on the results of BiomeBGC MCE completed before.
The BiomeBGC Projects Database & Management System was developed to easy prepare, manage and share all of the above mentioned datasets (files), investigations and provide interaction with Taverna workflows. Learn more about BBGCDB at http://ecos.okologia.mta.hu/bbgcdb/. 
Dependencies (0)
Processors (6)
Name 
Type 
Description 
Interaction2 
interaction 

model_calibration_ws 
rest 

GetURL 
beanshell 
Scripturl="http://ecos.okologia.mta.hu/bbgcdb/node/"+prID; 
message 
beanshell 
Scriptout1="The Glue project (project id: "+prID+") has been submitted."; 
trimID 
beanshell 

Interaction1 
interaction 

Beanshells (3)
Name 
Description 
Inputs 
Outputs 
GetURL 

prID

url

message 

prID

out1

trimID 

id1

out1

Outputs (3)
Name 
Description 
GLUE_ProjectID 
A unique numeric ID to identify the BiomeBGC GLUE project run in the BBGC database.

URL 
The URL of the BiomeBGC Project Database & Management System record created by the workflow.

Message 
Output message of the workflow about the run.

Datalinks (8)
Source 
Sink 
Interaction1:myOutput 
Interaction2:in1 
Interaction2:myOutput 
model_calibration_ws:nid 
trimID:out1 
GetURL:prID 
trimID:out1 
message:prID 
model_calibration_ws:responseBody 
trimID:id1 
trimID:out1 
GLUE_ProjectID 
GetURL:url 
URL 
message:out1 
Message 
Uploader
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Version 2 (latest)
(of 2)
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