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config.yaml
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######################################################
# Global attributes
data_folder:
ufhpc: /home/shawntaylor/data/phenology_forecasting/
default: /home/shawn/data/phenology_forecasting/
tmp_folder: tmp/
mask_file: land_mask.nc
google_auth: /home/shawn/.google_cloud_auth/phenology_updater.json
# holds status messages and details about the automated run.
# useful when different aspects of the automated pipeline are
# on different systems. currently configured for the hipergator.
run_status: /home/shawntaylor/run_info.json
slurm_job_script: phenology_forecasts/automated_forecast_job.sh
remote_connection_info:
host: hpg.rc.ufl.edu
user: shawntaylor
# Number of processes to use the pyPhenology.model.predict() method.
# Because predict() works on the CFSv2 forecasts, the memory usage for
# each process is quit large, 5-10GB.
n_jobs: 2
#######################################################
# Phenology models attributes
species_range_file: species_ranges.nc
phenology_model_folder: phenology_models/
phenology_forecast_folder: phenology_forecasts/
phenology_hindcast_folder: phenology_hindcasts/
species_list_file: species_list.csv
phenology_model_metadata_file: phenology_model_metadata.csv
phenology_observations_folder: phenology_observations/
phenology_naive_model_file: phenology_naive_models.nc
# This holds the yearly phenology predictions which calculate the long term average below
long_term_average_folder: long_term_averages/
phenology_long_term_averages_file: phenology_long_term_averages.nc
phenology_observations_temperature_file: phenology_observations/observation_temperatures.csv
phenology_forecast_figure_folder: phenology_static_images/
phenology_forecast_figure_metadata_file: phenology_static_image_metadata.csv
# prism data for building phenology models
daily_prism_folder: prism_daily_data/
# range map stuff
biolcim_folder: bioclim/
######################################################
# Climate models attributes
variables_to_use:
tmean:
cfs_nc_name: TMP_P0_L103_GGA0
cfs_file_prefix: tmp2m
prism_name: tmean
# precip:
# cfs_name: prpwtr
# prism_name: prp
season_month_begin: '11'
season_day_begin: '01'
historic_years_begin: 1995
historic_years_end: 2015
historic_observations_file: historic_observations.nc
historic_observations_folder: historic_observations/
historic_reanalysis_folder: historic_reanalysis/
current_season_observations_file: current_season_observations.nc
prism_cache_folder: prism_cache/
current_forecast_folder: current_forecasts/
historic_forecasts_file: historic_forecasts.nc
downscaling_model_coefficients_file: model_coefficients.nc
cfs_forecast_provenance_note: >
CFSv2 forecast from {download_url} obtained on {today}. Downscaled to 4km
resolution using asynchronous regression with PRISM as the observed
temperature. Dates {season_start} to {yesterday} are observed values
from the PRISM dataset at www.prism.oregonstate.edu.