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…param Issue200 final tweaks on sample param
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doc/parameter_files/input_parameter_file_all_options.py
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| ################################################################################ | ||
| # OPTIONS ARE SET BY USER IN THIS FILE AS INDICATED BELOW: | ||
| ################################################################################ | ||
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| ## METRICS RUN IDENTIFICATION | ||
| case_id = 'sampletest_140910' ; # Defines a subdirectory to output metrics results so multiple runs can be compared | ||
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| ## LIST OF MODEL VERSIONS TO BE TESTED - WHICH ARE EXPECTED TO BE PART OF CLIMATOLOGY FILENAME | ||
| model_versions = ['GFDL-CM4',] ; # ['GFDL-ESM2G',] ; # Model identifier | ||
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| ## Below are the STANDARD keys that the main code will be looking for | ||
| period = '000101-000112' ; # Model climatological period (if relevant) | ||
| realization = 'r1i1p1' ; # Model run identifier (if relevant) | ||
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| ## MODEL SPECIFIC PARAMETERS | ||
| model_tweaks = { | ||
| ## Keys are model acronym or None which applies to all model entries | ||
| None : { | ||
| ## Variable name mapping - map your model var names to CMIP5 official names | ||
| "variable_mapping" : { "tos" : "tos"}, | ||
| }, | ||
| "GFDL-ESM2G" : { | ||
| "variable_mapping" : { "tas" : "tas_ac"}, | ||
| }, | ||
| } | ||
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| ## VARIABLES AND OBSERVATIONS AVAILABLE FOR USE | ||
| # Variable acronyms are described in the CMIP5 standard output document - http://cmip-pcmdi.llnl.gov/cmip5/docs/standard_output.pdf | ||
| # 2d atmos variables | ||
| # vars = ['clt','hfss','pr','prw','psl','rlut','rlutcs','rsdt','rsut','rsutcs','tas','tauu','tauv','ts','uas','vas'] | ||
| # 3d atmos variables | ||
| # vars = ['hur','hus','huss','ta','ua','va','zg'] | ||
| # 3d atmos variables - example heights | ||
| # vars = ['hus_850','ta_850','ta_200','ua_850','ua_200','va_850','va_200','zg_500'] | ||
| # 2d ocean variables | ||
| # vars = ['sos','tos','zos'] | ||
| # Non-standard CMIP5 variables (available from obs output) | ||
| # vars = ['rlwcrf','rswcrf'] | ||
| # vars for processing | ||
| vars = ['pr','psl','rlut','rlutcs','rsut','rsutcs','ta_200','ta_850','tas','ua_200','ua_850','va_200','va_850','zg_500'] | ||
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| # Observations to use 'default', 'alternate', 'all or specific enumerated climatology e.g. 'ref3' | ||
| ref = ['default'] #,'all','alternate','ref3' | ||
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| ## INTERPOLATION OPTIONS | ||
| targetGrid = '2.5x2.5' # Options: '2.5x2.5' or an actual cdms2 grid object | ||
| regrid_tool = 'regrid2' # Options: 'regrid2','esmf' | ||
| regrid_method = 'linear' # Options: 'linear','conservative', only if tool is esmf | ||
| regrid_tool_ocn = 'esmf' # Options: 'regrid2','esmf' - Note regrid2 will fail with non lat/lon grids | ||
| regrid_method_ocn = 'linear' # Options: 'linear','conservative', only if tool is esmf | ||
| save_mod_clims = True # Options: True or False (Save interpolated model climatologies used in metrics calculations) | ||
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| ## DATA LOCATION: MODELS, OBS AND METRICS OUTPUT - AND TEMPLATES FOR MODEL OUTPUT CLIMATOLOGY FILES | ||
| ## Following are custom keys specific to your local system | ||
| ## it is a python dictionary | ||
| ## keys are your custom keys, the "value" for this key is actually defined by another dictionary | ||
| ## This second dictionary maps the key value to each specific variable | ||
| ## use None if you want a value to be used for every variables not specifically defined | ||
| custom_keys = { "key1": {None:"key1_value_for_all_vars", "tas" : "key1_value_for_tas"}, } | ||
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| ## By default file names are constructed using the following keys: | ||
| ## %(variable) # set by driver - this loops over all variables specified in vars list above | ||
| ## %(realm) | ||
| ## %(table) # CMIP standard table id - e.g. Amon (Atmosphere monthly), Omon (Ocean monthly) | ||
| ## %(level) # extracted by driver from vars list defined above | ||
| ## %(model_version) # set by driver from model_versions list defined above | ||
| ## %(realization) # Model realization information - e.g. r1i1p1 | ||
| ## %(period) # Time period of analysis | ||
| ## %(ext) # Output file extension | ||
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| ## Templates for input climatology files | ||
| ## TEMPLATE EXAMPLE (once constructed) : | ||
| ## tas: tas_GFDL-ESM2G_Amon_historical_r1i1p1_198001-199912_key1_value_for_tas-clim.nc | ||
| ## tos: tos_GFDL-ESM2G_Omon_historical_r1i1p1_198001-199912_key1_value_for_all_vars-clim.nc | ||
| filename_template = "%(variable)_%(model_version)_%(table)_historical_%(realization)_%(period)_%(key1)-clim.nc" | ||
| ## filename template for input landsea masks ('sftlf') | ||
| sftlf_filename_template = "sftlf_%(model_version).nc" | ||
| ## Do we generate sftlf if file not found? | ||
| ## default is False | ||
| generate_sftlf = True | ||
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| # ROOT PATH FOR MODELS CLIMATOLOGIES | ||
| mod_data_path = '/export/durack1/140701_metrics/test_new' | ||
| # ROOT PATH FOR OBSERVATIONS | ||
| obs_data_path = '/export/durack1/140701_metrics/obs' | ||
| # DIRECTORY WHERE TO PUT RESULTS - will create case_id subdirectory | ||
| metrics_output_path = '/export/durack1/140701_metrics/test_new' | ||
| # DIRECTORY WHERE TO PUT INTERPOLATED MODELS' CLIMATOLOGIES - will create case_id subdirectory | ||
| model_clims_interpolated_output = '/export/durack1/140701_metrics/test_new' | ||
| # FILENAME FOR INTERPOLATED CLIMATOLOGIES OUTPUT | ||
| filename_output_template = "%(variable)%(level)_%(model_version)_%(table)_historical_%(realization)_%(period)_interpolated_%(regridMethod)_%(targetGridName)-clim%(ext)" | ||
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| ## CUSTOM METRICS | ||
| ## The following examples allow users to plug in a set of custom metrics | ||
| ## Function needs: | ||
| ## INPUT: var name, model clim, obs clim | ||
| ## OUTPUT: dictionary | ||
| ## dict pairs are: { metrics_name:float } | ||
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| import pcmdi_metrics # Or whatever your custom metrics package name is | ||
| compute_custom_metrics = pcmdi_metrics.pcmdi.compute_metrics | ||
| #or | ||
| def mymax(slab,nm): | ||
| return {"custom_%s_max" % nm:float(slab.max())} | ||
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| def mymin(slab,nm): | ||
| return {"custom_%s_min" % nm:float(slab.min())} | ||
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| def my_custom(var,dm,do): | ||
| out = {} | ||
| for f in [mymax,mymin]: | ||
| out.update(f(dm,"model")) | ||
| out.update(f(dm,"ref")) | ||
| out["some_custom"]=1.5 | ||
| return out | ||
| compute_custom_metrics = my_custom |
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