File size: 1,783 Bytes
73ddb67 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | format_version: ml_modis_npz_v1
data:
path: data/ml_modis_fake.npz
samples: 1400
years: [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]
months: [9, 10]
platforms: [Terra, Aqua]
dimensions:
predictors: 114
targets: 4
variables:
profile:
names: [temperature, specific_humidity, relative_humidity, u_wind, v_wind, omega, geopotential, cloud_liquid, cloud_fraction]
pressure_levels_hpa: [1000, 950, 900, 850, 800, 750, 700, 650, 600, 550]
count: 90
single_level:
names: [sst, surface_pressure, mslp, skin_temperature, t2m, d2m, u10, v10, surface_solar_radiation, surface_thermal_radiation, latent_heat_flux, sensible_heat_flux, boundary_layer_height, total_column_water_vapour, total_column_cloud_liquid, cape, cin, low_cloud_cover, sea_ice_fraction, precipitation, cos_sza, latitude, longitude, platform_hour]
count: 24
targets:
names: [Nd, reff, LWP, CF]
units: [cm-3, um, g-m-2, fraction]
coordinates:
latitude_degrees_north: [45, 75]
longitude_degrees_east: [-60, 30]
model:
trees: 12
max_depth: 9
min_leaf: 7
max_features: 38
bootstrap_fraction: 0.6
split_candidates: 12
paper_model:
trees: 100
max_depth: null
min_leaf: 7
max_features: 38
bootstrap_fraction: 0.6
split_candidates: 12
train:
excluded_year: 2014
independent_models: 8
runtime:
seed: 20220908
device: cpu
distributed_backend: gloo
paths:
checkpoint: result/checkpoints/ml_modis.pt
training_metrics: result/training/metrics.json
predictions: result/output/predictions.npz
evaluation_dir: result/evaluation
evaluation:
cloud_albedo: 0.38
clear_sky_ocean_albedo: 0.07
importance_top_k: 10
figure_dpi: 150
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