Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Land sea mask generation #1006

Merged
merged 11 commits into from
Dec 18, 2023
Merged

Land sea mask generation #1006

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
11 commits
Select commit Hold shift + click to select a range
a6025f2
first commit
lee1043 Dec 15, 2023
27ee3dc
modularize target grid and land sea mask generations, remove CDAT com…
lee1043 Dec 16, 2023
ac74c96
pre-commit fix
lee1043 Dec 16, 2023
da35f2a
replace cdutil generate land sea mask to the regionmask-based new fun…
lee1043 Dec 16, 2023
7710087
pre-commit fix
lee1043 Dec 16, 2023
471bdda
copy sort_human function to utils
lee1043 Dec 16, 2023
019e497
remove width=0.5 that is deprecated in xcdat latest version
lee1043 Dec 16, 2023
51434ef
update documentation
lee1043 Dec 17, 2023
69883ef
apply landmask function added, clean up
lee1043 Dec 17, 2023
33c7df9
clean up
lee1043 Dec 17, 2023
2a7d98f
clean up
lee1043 Dec 17, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
165 changes: 56 additions & 109 deletions pcmdi_metrics/mean_climate/mean_climate_driver.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,11 +6,6 @@
from collections import OrderedDict
from re import split

import cdms2
import cdutil
import numpy as np
import xcdat as xc

from pcmdi_metrics import resources
from pcmdi_metrics.io import load_regions_specs, region_subset
from pcmdi_metrics.mean_climate.lib import (
Expand All @@ -19,8 +14,11 @@
load_and_regrid,
mean_climate_metrics_to_json,
)
from pcmdi_metrics.utils import apply_landmask, create_land_sea_mask, create_target_grid
from pcmdi_metrics.variability_mode.lib import sort_human, tree

print("--- prepare mean climate metrics calculation ---")

parser = create_mean_climate_parser()
parameter = parser.get_parameter(argparse_vals_only=False)

Expand Down Expand Up @@ -78,103 +76,45 @@
regions_specs = load_regions_specs()

default_regions = ["global", "NHEX", "SHEX", "TROPICS"]
print(
"case_id: ",
case_id,
"\n",
"test_data_set:",
test_data_set,
"\n",
"realization:",
realization,
"\n",
"vars:",
vars,
"\n",
"varname_in_test_data:",
varname_in_test_data,
"\n",
"reference_data_set:",
reference_data_set,
"\n",
"target_grid:",
target_grid,
"\n",
"regrid_tool:",
regrid_tool,
"\n",
"regrid_tool_ocn:",
regrid_tool_ocn,
"\n",
"save_test_clims:",
save_test_clims,
"\n",
"test_clims_interpolated_output:",
test_clims_interpolated_output,
"\n",
"filename_template:",
filename_template,
"\n",
"sftlf_filename_template:",
sftlf_filename_template,
"\n",
"generate_sftlf:",
generate_sftlf,
"\n",
"regions_specs:",
regions_specs,
"\n",
"regions:",
regions,
"\n",
"test_data_path:",
test_data_path,
"\n",
"reference_data_path:",
reference_data_path,
"\n",
"metrics_output_path:",
metrics_output_path,
"\n",
"diagnostics_output_path:",
diagnostics_output_path,
"\n",
"debug:",
debug,
"\n",

config_variables = OrderedDict(
[
("case_id", case_id),
("test_data_set", test_data_set),
("realization", realization),
("vars", vars),
("varname_in_test_data", varname_in_test_data),
("reference_data_set", reference_data_set),
("target_grid", target_grid),
("regrid_tool", regrid_tool),
("regrid_tool_ocn", regrid_tool_ocn),
("save_test_clims", save_test_clims),
("test_clims_interpolated_output", test_clims_interpolated_output),
("filename_template", filename_template),
("sftlf_filename_template", sftlf_filename_template),
("generate_sftlf", generate_sftlf),
("regions_specs", regions_specs),
("regions", regions),
("test_data_path", test_data_path),
("reference_data_path", reference_data_path),
("metrics_output_path", metrics_output_path),
("diagnostics_output_path", diagnostics_output_path),
("debug", debug),
]
)

print("--- prepare mean climate metrics calculation ---")
for key, value in config_variables.items():
print(f"{key}: {value}")

# generate target grid
res = target_grid.split("x")
lat_res = float(res[0])
lon_res = float(res[1])
start_lat = -90.0 + lat_res / 2
start_lon = 0.0
end_lat = 90.0 - lat_res / 2
end_lon = 360.0 - lon_res
nlat = ((end_lat - start_lat) * 1.0 / lat_res) + 1
nlon = ((end_lon - start_lon) * 1.0 / lon_res) + 1
t_grid = xc.create_uniform_grid(
start_lat, end_lat, lat_res, start_lon, end_lon, lon_res
)
if debug:
print(
"type(t_grid):", type(t_grid)
) # Expected type is 'xarray.core.dataset.Dataset'
print("t_grid:", t_grid)
# identical target grid in cdms2 to use generateLandSeaMask function that is yet to exist in xcdat
t_grid_cdms2 = cdms2.createUniformGrid(
start_lat, nlat, lat_res, start_lon, nlon, lon_res
)
t_grid = create_target_grid(target_grid_resolution=target_grid)

# generate land sea mask for the target grid
sft = cdutil.generateLandSeaMask(t_grid_cdms2)
if debug:
print("sft:", sft)
print("sft.getAxisList():", sft.getAxisList())
sft = create_land_sea_mask(t_grid)

# add sft to target grid dataset
t_grid["sftlf"] = (["lat", "lon"], np.array(sft))
t_grid["sftlf"] = sft

if debug:
print("t_grid (after sftlf added):", t_grid)
t_grid.to_netcdf("target_grid.nc")
Expand All @@ -188,8 +128,6 @@
obs_file_path = os.path.join(egg_pth, obs_file_name)
with open(obs_file_path) as fo:
obs_dict = json.loads(fo.read())
# if debug:
# print('obs_dict:', json.dumps(obs_dict, indent=4, sort_keys=True))

print("--- start mean climate metrics calculation ---")

Expand Down Expand Up @@ -353,26 +291,35 @@
print("region:", region)

# land/sea mask -- conduct masking only for variable data array, not entire data
if ("land" in region.split("_")) or (
"ocean" in region.split("_")
if any(
keyword in region.split("_")
for keyword in ["land", "ocean"]
):
ds_test_tmp = ds_test.copy(deep=True)
ds_ref_tmp = ds_ref.copy(deep=True)
if "land" in region.split("_"):
ds_test_tmp[varname] = ds_test[varname].where(
t_grid["sftlf"] != 0.0
ds_test_tmp[varname] = apply_landmask(
ds_test[varname],
landfrac=t_grid["sftlf"],
keep_over="land",
)
ds_ref_tmp[varname] = ds_ref[varname].where(
t_grid["sftlf"] != 0.0
ds_ref_tmp[varname] = apply_landmask(
ds_ref[varname],
landfrac=t_grid["sftlf"],
keep_over="land",
)
elif "ocean" in region.split("_"):
ds_test_tmp[varname] = ds_test[varname].where(
t_grid["sftlf"] == 0.0
ds_test_tmp[varname] = apply_landmask(
ds_test[varname],
landfrac=t_grid["sftlf"],
keep_over="ocean",
)
ds_ref_tmp[varname] = ds_ref[varname].where(
t_grid["sftlf"] == 0.0
ds_ref_tmp[varname] = apply_landmask(
ds_ref[varname],
landfrac=t_grid["sftlf"],
keep_over="ocean",
)
print("mask done")
print("mask done")
else:
ds_test_tmp = ds_test
ds_ref_tmp = ds_ref
Expand Down
17 changes: 7 additions & 10 deletions pcmdi_metrics/precip_variability/lib/lib_variability_across_timescales.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,6 @@
import os
import sys

import cdutil
import numpy as np
import pandas as pd
import xarray as xr
Expand All @@ -12,7 +11,8 @@
from scipy.stats import chi2
from xcdat.regridder import grid

import pcmdi_metrics
from pcmdi_metrics.io.base import Base
from pcmdi_metrics.utils import create_land_sea_mask


# ==================================================================================
Expand Down Expand Up @@ -94,9 +94,7 @@ def precip_variability_across_timescale(
outfilename = (
"PS_pr." + str(dfrq) + "_regrid.180x90_area.freq.mean_" + dat + ".json"
)
JSON = pcmdi_metrics.io.base.Base(
outdir.replace("%(output_type)", "metrics_results"), outfilename
)
JSON = Base(outdir.replace("%(output_type)", "metrics_results"), outfilename)
JSON.write(
psdmfm,
json_structure=["model+realization", "variability type", "domain", "frequency"],
Expand Down Expand Up @@ -389,9 +387,8 @@ def Avg_PS_DomFrq(d, frequency, ntd, dat, mip, frc):
else:
sys.exit("ERROR: frc " + frc + " is not defined!")

d_cdms = xr.DataArray.to_cdms2(d[0])
mask = cdutil.generateLandSeaMask(d_cdms)
mask = xr.DataArray.from_cdms2(mask)
# generate land sea mask
mask = create_land_sea_mask(d[0])

psdmfm = {}
for dom in domains:
Expand All @@ -405,8 +402,8 @@ def Avg_PS_DomFrq(d, frequency, ntd, dat, mip, frc):
dmask = d

dmask = dmask.to_dataset(name="ps")
dmask = dmask.bounds.add_bounds(axis="X", width=0.5)
dmask = dmask.bounds.add_bounds(axis="Y", width=0.5)
dmask = dmask.bounds.add_bounds(axis="X")
dmask = dmask.bounds.add_bounds(axis="Y")

if "50S50N" in dom:
am = dmask.sel(lat=slice(-50, 50)).spatial.average(
Expand Down
3 changes: 3 additions & 0 deletions pcmdi_metrics/utils/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,3 @@
from .create_land_sea_mask import apply_landmask, create_land_sea_mask
from .create_target_grid import create_target_grid
from .sort_human import sort_human
Loading
Loading