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Update constants and when they are used for GFS #372

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Update constants and when they are used for GFS #372

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a20036d
Update constants and when they are used for GFS
Dec 19, 2024
602f87b
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Dec 23, 2024
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9 changes: 8 additions & 1 deletion ocf_datapipes/training/pvnet_site.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@

import logging
from datetime import datetime, timedelta
from functools import partial
from typing import List, Optional

import xarray as xr
Expand Down Expand Up @@ -237,12 +238,18 @@ def construct_sliced_data_pipeline(
roi_width_pixels=conf_nwp[nwp_key].nwp_image_size_pixels_width,
)
# Coarsen the data, if it is separated by 0.05 degrees each
nwp_datapipe = nwp_datapipe.map(potentially_coarsen)
potentially_coarsen_partial = partial(
potentially_coarsen, coarsen_to_deg=conf_nwp[nwp_key].coarsen_to_degrees
)
nwp_datapipe = nwp_datapipe.map(potentially_coarsen_partial)
# Somewhat hacky way for India specifically, need different mean/std for ECMWF data
if conf_nwp[nwp_key].nwp_provider in ["ecmwf"]:
normalize_provider = "ecmwf_india"
elif conf_nwp[nwp_key].nwp_provider in ["gfs"]:
normalize_provider = "gfs_india"
else:
normalize_provider = conf_nwp[nwp_key].nwp_provider

nwp_datapipes_dict[nwp_key] = nwp_datapipe.normalize(
mean=NWP_MEANS[normalize_provider],
std=NWP_STDS[normalize_provider],
Expand Down
75 changes: 68 additions & 7 deletions ocf_datapipes/utils/consts.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,6 +39,7 @@ def __getitem__(self, key):
NWP_PROVIDERS = [
"ukv",
"gfs",
"gfs_india",
"icon-eu",
"icon-global",
"ecmwf",
Expand Down Expand Up @@ -132,17 +133,32 @@ def __getitem__(self, key):
UKV_STD = _to_data_array(UKV_STD)
UKV_MEAN = _to_data_array(UKV_MEAN)

# These were calculated from 200 random init times (step 0s) from the MO global data
# --- MO Global

MO_GLOBAL_INDIA_MEAN = {
"temperature_sl": 298.2,
"wind_u_component_10m": 0.5732,
"wind_v_component_10m": -0.2831,
"temperature_sl": 295.34392488,
"wind_u_component_10m": 0.83223102,
"wind_v_component_10m": 0.0802083,
"downward_shortwave_radiation_flux_gl": 225.54222068,
"cloud_cover_high": 0.34935897,
"cloud_cover_low": 0.096081,
"cloud_cover_medium": 0.13878676,
"relative_humidity_sl": 69.59633137,
"snow_depth_gl": 3.45158744,
"visibility_sl": 23181.81547681,
}

MO_GLOBAL_INDIA_STD = {
"temperature_sl": 8.473,
"wind_u_component_10m": 2.599,
"wind_v_component_10m": 2.016,
"temperature_sl": 12.26983825,
"wind_u_component_10m": 3.45169835,
"wind_v_component_10m": 2.9825603,
"downward_shortwave_radiation_flux_gl": 303.85182864,
"cloud_cover_high": 0.40563507,
"cloud_cover_low": 0.18374192,
"cloud_cover_medium": 0.25972151,
"relative_humidity_sl": 21.00264399,
"snow_depth_gl": 30.19116501,
"visibility_sl": 5385.35839715,
}


Expand Down Expand Up @@ -197,6 +213,48 @@ def __getitem__(self, key):
GFS_MEAN = _to_data_array(GFS_MEAN)


# ------ GFS
GFS_INDIA_STD_DICT = {
"t": 14.93798,
"prate": 5.965701e-05,
"u10": 3.4826114,
"v10": 3.167296,
"u100": 4.140226,
"v100": 3.984121,
"dlwrf": 79.30329,
"dswrf": 325.58582,
"hcc": 39.91955,
"lcc": 23.208075,
"mcc": 33.283035,
"r": 25.545837,
"sde": 0.10192183,
"tcc": 42.583195,
"vis": 3491.437,
}
GFS_INDIA_MEAN_DICT = {
"t": 298.27713,
"prate": 1.7736e-05,
"u10": 1.5782778,
"v10": 0.09856875,
"u100": 1.4558668,
"v100": -0.28256148,
"dlwrf": 356.57776,
"dswrf": 284.358,
"hcc": 26.965801,
"lcc": 9.2288,
"mcc": 17.2132,
"r": 38.2474,
"sde": 0.02070413,
"tcc": 36.962795,
"vis": 23386.936,
}


GFS_INDIA_VARIABLE_NAMES = tuple(GFS_INDIA_MEAN_DICT.keys())
GFS_INDIA_STD = _to_data_array(GFS_INDIA_STD_DICT)
GFS_INDIA_MEAN = _to_data_array(GFS_INDIA_MEAN_DICT)


# ------ ECMWF
# These were calculated from 100 random init times of UK data from 2020-2023
ECMWF_STD = {
Expand Down Expand Up @@ -369,6 +427,7 @@ def __getitem__(self, key):
NWP_VARIABLE_NAMES = NWPStatDict(
ukv=UKV_VARIABLE_NAMES,
gfs=GFS_VARIABLE_NAMES,
gfs_india=GFS_INDIA_VARIABLE_NAMES,
ecmwf=ECMWF_VARIABLE_NAMES,
ecmwf_india=INDIA_ECMWF_VARIABLE_NAMES,
excarta=EXCARTA_VARIABLE_NAMES,
Expand All @@ -379,6 +438,7 @@ def __getitem__(self, key):
NWP_STDS = NWPStatDict(
ukv=UKV_STD,
gfs=GFS_STD,
gfs_india=GFS_INDIA_STD,
ecmwf=ECMWF_STD,
ecmwf_india=INDIA_ECMWF_STD,
excarta=EXCARTA_STD,
Expand All @@ -389,6 +449,7 @@ def __getitem__(self, key):
NWP_MEANS = NWPStatDict(
ukv=UKV_MEAN,
gfs=GFS_MEAN,
gfs_india=GFS_INDIA_MEAN,
ecmwf=ECMWF_MEAN,
ecmwf_india=INDIA_ECMWF_MEAN,
excarta=EXCARTA_MEAN,
Expand Down
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