blob: 15b099455852baf0fef702aad2c3e004e8411fed [file] [log] [blame]
workdir: ./
output_netcdf_filename: dscale_prmo_wus_NDJFM_2000-2004.nc
# (RCMES will temporally subset data between month_start and month_end. If average_each_year is True (False), seasonal mean in each year is (not) calculated and used for metrics calculation.)
time:
maximum_overlap_period: False
start_time: 2001-01-01
end_time: 2004-12-31
temporal_resolution: monthly
month_start: 11
month_end: 3
average_each_year: True
space:
min_lat: 25.063
max_lat: 49.063
min_lon: -124.938
max_lon: -100.938
regrid:
regrid_on_reference: False
regrid_dlat: 0.125
regrid_dlon: 0.125
datasets:
- loader_name: rcmed
name: TRMM
dataset_id: 3
parameter_id: 36
variable_name: pr
- loader_name: local
file_path: ./data/dscale/prmo*.nc
variable_name: pr
number_of_metrics_and_plots: 2
metrics1: Map_plot_bias_of_multiyear_climatology
plots1:
file_name: BIAS_prmo-wus_NDJFM_vs_trmm
subplots_array: !!python/tuple [3,3]
metrics2: Taylor_diagram_spatial_pattern_of_multiyear_climatology
plots2:
file_name: TD_prmo-wus_NDJFM_vs_trmm
use_subregions: False
#subregions:
##subregion name (R01, R02, R03,....) followed by an array of boundaries [south, north, west, east]
# R01:
# [42.75, 49.75, -123.75, -120.25]
# R02:
# [42.75, 49.75, -119.75, -112.75]
# R03:
# [37.25, 42.25, -123.75, -117.75]
# R04:
# [32.25, 37.25, -122.75, -114.75]
# R05:
# [31.25, 37.25, -113.75, -108.25]
# R06:
# [31.25, 37.25, -108.25, -99.75]
# R07:
# [37.25, 43.25, -110.25, -103.75]
# R08:
# [45.25, 49.25, -99.75, -90.25]
# R09:
# [34.75, 45.25, -99.75, -90.25]
# R10:
# [29.75, 34.75, -95.75, -84.75]
# R11:
# [38.25, 44.75, -89.75, -80.25]
# R12:
# [38.25, 44.75, -79.75, -70.25]
# R13:
# [30.75, 38.25, -83.75, -75.25]
# R14:
# [24.25, 30.75, -83.75, -80.25]