From 41d20fa079d7ad0fb03e5b67db41ff57b756c48a Mon Sep 17 00:00:00 2001 From: Zwart Date: Tue, 1 Jun 2021 14:42:32 -0400 Subject: [PATCH] updating metadata for stream forecast --- metadata/aquatics-2021-05-01-BTW.yml | 96 ++++++++++++++-------------- 1 file changed, 48 insertions(+), 48 deletions(-) diff --git a/metadata/aquatics-2021-05-01-BTW.yml b/metadata/aquatics-2021-05-01-BTW.yml index 62f6655..4b32673 100644 --- a/metadata/aquatics-2021-05-01-BTW.yml +++ b/metadata/aquatics-2021-05-01-BTW.yml @@ -63,16 +63,16 @@ metadata: #species in a community model, number of age/size classes in a population model, #number of pools in a biogeochemical model. initial_conditions: - status: absent #options: absent, present, data_driven, propagates, assimilates - complexity: 0 #How many models states need initial conditions + status: assimilates #options: absent, present, data_driven, propagates, assimilates + complexity: 1 #How many models states need initial conditions propagation: type: ensemble #How does your model propogate initial conditions (ensemble or MCMC is most common) - size: 2000. #number of ensemble or MCMC members + size: 31 #number of ensemble or MCMC members #Leave everything below blank UNLESS status = assimilates assimilation: - type: refit #description of assimilation method - reference: "NA" #reference for assimilation method - complexity: 4 #number of states that are updated with assimilation + type: EnKF #description of assimilation method + reference: https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10302 #reference for assimilation method + complexity: 1 #number of states that are updated with assimilation # #DRIVERS #uncertainty in model drivers, covariates, and exogenous scenarios (X). @@ -85,17 +85,17 @@ metadata: #model, this would be the number of climate inputs (temperature, precip, solar #radiation, etc.). drivers: - status: present #options: absent, present, data_driven, propagates, assimilates + status: propogates #options: absent, present, data_driven, propagates, assimilates complexity: 1 #How many drivers are used? #Leave everything below blank if status = absent, present, or data_driven propagation: type: ensemble #How does your model propogate driver (ensemble or MCMC is most common) size: 31 #number of ensemble or MCMC members #Leave everything below blank UNLESS status = assimilates - assimilation: - type: refit #description of assimilation method - reference: "none" #reference for assimilation method - complexity: 4 #number of states that are updated with assimilation + # assimilation: + # type: EnKF #description of assimilation method + # reference: https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10302 #reference for assimilation method + # complexity: #number of states that are updated with assimilation # #PARAMETERS #Uncertainty in model parameters (). For most ecological processes the parameters @@ -108,14 +108,14 @@ metadata: status: present #options: absent, present, data_driven, propagates, assimilates complexity: 2 #Leave everything below blank if status = absent, present, or data_driven - propagation: - type: ensemble #how does your model propogate parameter uncertainity? - size: 2000 - #Leave everything below blank UNLESS status = assimilates - assimilation: - type: refit - reference: "none" - complexity: 4 + # propagation: + # type: ensemble #how does your model propogate parameter uncertainity? + # size: 2000 + # #Leave everything below blank UNLESS status = assimilates + # assimilation: + # type: refit + # reference: "none" + # complexity: 4 # #RANDOM EFFECTS #Unexplained variability and heterogeneity in model parameters (). Hierarchical @@ -135,16 +135,16 @@ metadata: # random_effects: status: absent #options: absent, present, data_driven, propagates, assimilates - complexity: 2 - #Leave everything below blank if status = absent, present, or data_driven - propagation: - type: ensemble #How does your model propogate random effects (ensemble or MCMC is most common) - size: 2000 #number of ensemble or MCMC members - #Leave everything below blank UNLESS status = assimilates - assimilation: - type: refit #description of assimilation method - reference: "none" #reference for assimilation method - complexity: 4 #number of states that are updated with assimilation + # complexity: 2 + # #Leave everything below blank if status = absent, present, or data_driven + # propagation: + # type: ensemble #How does your model propogate random effects (ensemble or MCMC is most common) + # size: 2000 #number of ensemble or MCMC members + # #Leave everything below blank UNLESS status = assimilates + # assimilation: + # type: refit #description of assimilation method + # reference: "none" #reference for assimilation method + # complexity: 4 #number of states that are updated with assimilation # #PROCESS ERROR #Dynamic uncertainty in the process model () attributable to both model @@ -157,18 +157,18 @@ metadata: #match the dimensionality of the initial_conditions unless there are state #variables where process error is not being estimated or propagated process_error: - status: absent #options: absent, present, data_driven, propagates, assimilates - complexity: 2 #Leave blank if status = absent + status: assimilates #options: absent, present, data_driven, propagates, assimilates + complexity: 1 #Leave blank if status = absent #Leave everything below blank if status = absent, present, or data_driven propagation: type: ensemble #How does your model propogate random effects uncertainty (ensemble or MCMC is most common) - size: 2000 + size: 31 #Leave everything below blank UNLESS status = assimilates assimilation: - type: refit - reference: "none" - complexity: 4 - covariance: FALSE #TRUE OR FALSE + type: EnKF + reference: https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10302 + complexity: 1 + covariance: TRUE #TRUE OR FALSE localization: FALSE # #OBSERVATION ERROR @@ -185,16 +185,16 @@ metadata: #match the dimensionality of the initial_conditions unless there are state #variables where process error is not being estimated or propagated obs_error: - status: absent #options: absent, present, data_driven, propagates, assimilates - complexity: 2 #Leave blank if status = absent + status: data_driven #options: absent, present, data_driven, propagates, assimilates + complexity: 1 #Leave blank if status = absent #Leave everything below blank if status = absent, present, or data_driven - propagation: - type: ensemble #How does your model propogate observation error (ensemble or MCMC is most common) - size: 31. #number of ensemble or MCMC members - #Leave everything below blank UNLESS status = assimilates - assimilation: - type: refit #description of assimilation method - reference: "none" #reference for assimilation method - complexity: 4 #number of states that are updated with assimilation - covariance: FALSE #TRUE OR FALSE - localization: FALSE + # propagation: + # type: ensemble #How does your model propogate observation error (ensemble or MCMC is most common) + # size: 31. #number of ensemble or MCMC members + # #Leave everything below blank UNLESS status = assimilates + # assimilation: + # type: refit #description of assimilation method + # reference: "none" #reference for assimilation method + # complexity: 4 #number of states that are updated with assimilation + # covariance: FALSE #TRUE OR FALSE + # localization: FALSE