ML offline diagnostics

Report created 2023-11-16 15:04:25 PST

Metadata

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                    {
    "model_path": "/scratch/cimes/skclark/example/models/tq-model",
    "data_config": {
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                "nudging_variables": [
                    "air_temperature",
                    "specific_humidity",
                    "eastward_wind",
                    "northward_wind",
                    "pressure_thickness_of_atmospheric_layer"
                ]
            }
        },
        "variable_names": [
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            "surface_geopotential",
            "air_temperature",
            "specific_humidity",
            "eastward_wind",
            "northward_wind",
            "latitude",
            "dQ1",
            "dQ2",
            "dQu",
            "dQv"
        ],
        "timesteps_per_batch": 10,
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        "subsample_ratio": 1.0,
        "drop_nans": false,
        "shuffle_timesteps": false,
        "shuffle_samples": false,
        "data_transforms": null,
        "ptop": 300.0,
        "catalog_path": "/home/skclark/work/2023-11-15-cleaned-up-workflow/configs/catalog.yaml"
    },
    "commit": "a47261e19084a93108cea2d2c5b48ff59a2e5c5d",
    "training_config": {
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        },
        "derived_output_variables": [],
        "model_type": "dense",
        "output_transforms": [],
        "random_seed": 0,
        "sample_dim_name": "sample",
        "hyperparameters": {
            "callbacks": [
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                    "kwargs": {
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                        "patience": 25
                    },
                    "name": "EarlyStopping"
                }
            ],
            "clip_config": {
                "clip": {
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                        "step": null,
                        "stop": null
                    },
                    "dQ1": {
                        "start": 3,
                        "step": null,
                        "stop": null
                    },
                    "dQ2": {
                        "start": 3,
                        "step": null,
                        "stop": null
                    },
                    "specific_humidity": {
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                        "step": null,
                        "stop": null
                    }
                }
            },
            "dense_network": {
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                "gaussian_noise": 0,
                "kernel_regularizer": {
                    "kwargs": {
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                    "name": "l2"
                },
                "spectral_normalization": false,
                "width": 419
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            "input_variables": [
                "cos_zenith_angle",
                "surface_geopotential",
                "air_temperature",
                "specific_humidity",
                "latitude"
            ],
            "loss": {
                "loss_type": "mae",
                "scaling": "standard",
                "weight": 1
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            "normalization_fit_samples": 8000,
            "optimizer_config": {
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                "name": "Adam"
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            "output_limit_config": {
                "limits": {
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                    "dQ2": {
                        "max": 1.5e-06,
                        "min": -1.5e-06
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                }
            },
            "output_variables": [
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                "dQ2"
            ],
            "training_loop": {
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                "epochs": 500,
                "in_memory": true,
                "shuffle_buffer_size": 50000
            },
            "weights": null
        }
    },
    "training_data_config": {
        "catalog_path": "/home/skclark/work/2023-11-15-cleaned-up-workflow/configs/catalog.yaml",
        "mapper_config": {
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        "shuffle_samples": false,
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        "timesteps_per_batch": 10,
        "unstacked_dims": [
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        ],
        "variable_names": [
            "cos_zenith_angle",
            "surface_geopotential",
            "air_temperature",
            "specific_humidity",
            "eastward_wind",
            "northward_wind",
            "latitude",
            "dQ1",
            "dQ2",
            "dQu",
            "dQv"
        ]
    }
}
                

Metrics

Variable r2 bias
column_integrated_dq1_2d_global 2.88e-01 1.25e+00 [W/m2]
column_integrated_dq1_2d_land 2.51e-01 -1.04e+00 [W/m2]
column_integrated_dq1_2d_sea 3.20e-01 2.17e+00 [W/m2]
column_integrated_dq2_2d_global 2.21e-01 8.57e-02 [mm/day]
column_integrated_dq2_2d_land 2.14e-01 -5.72e-02 [mm/day]
column_integrated_dq2_2d_sea 2.23e-01 1.43e-01 [mm/day]
column_integrated_q2_2d_global 6.03e-01 8.57e-02 [mm/day]
column_integrated_q2_2d_land 4.83e-01 -5.72e-02 [mm/day]
column_integrated_q2_2d_sea 6.33e-01 1.43e-01 [mm/day]
water_vapor_path_2d_global 1.00e+00 0.00e+00 [mm]
water_vapor_path_2d_land 1.00e+00 0.00e+00 [mm]
water_vapor_path_2d_sea 1.00e+00 0.00e+00 [mm]

Links

Model input sensitivity Maps

Timesteps used for testing

Zonal averaged pressure level metrics

Pressure level metrics

Model level metrics

Vertical profiles of predicted variables on model levels

Diurnal cycles of column integrated quantities

Transect snapshot at lon=0 deg, 2020-02-19 01:30:00

Water vapor path versus column integrated drying