def test_fire_weather_ufunc_overwintering():
ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
ds = ds.assign(
rh=atmos.relative_humidity_from_dewpoint(ds=ds),
ws=convert_units_to(atmos.wind_speed_from_vector(ds=ds)[0], "km/h"),
tas=convert_units_to(ds.tas, "degC"),
pr=convert_units_to(ds.pr, "mm/d"),
)
season_mask_all = fire_season(ds.tas,
method="WF93",
temp_end_thresh="4 degC")
season_mask_all_LA08 = fire_season(ds.tas, snd=ds.swe, method="LA08")
season_mask_yr = fire_season(ds.tas, method="WF93", freq="YS")
# Mask is computed correctly and parameters are passed
# season not passed so computed on the fly
out1 = fire_weather_ufunc(
tas=ds.tas,
pr=ds.pr,
lat=ds.lat,
season_method="WF93",
overwintering=False,
temp_end_thresh=4,
indexes=["DC"],
)
np.testing.assert_array_equal(out1["season_mask"], season_mask_all)
out2 = fire_weather_ufunc(
tas=ds.tas,
pr=ds.pr,
snd=ds.swe,
lat=ds.lat,
season_method="LA08",
overwintering=True,
indexes=["DC"],
)
np.testing.assert_array_equal(out2["season_mask"], season_mask_all_LA08)
# Overwintering
# Get last season's DC (from previous comp) and mask Saskatoon and Victoria
dc0 = out2["DC"].ffill("time").isel(time=-1).where(
[True, True, True, False, False])
winter_pr = out2["winter_pr"]
out3 = fire_weather_ufunc(
tas=ds.tas,
pr=ds.pr,
lat=ds.lat,
winter_pr=winter_pr,
season_mask=season_mask_yr,
dc0=dc0,
overwintering=True,
indexes=["DC"],
)
np.testing.assert_allclose(out3["winter_pr"].isel(location=0),
261.27353647,
rtol=1e-6)
np.testing.assert_array_equal(out3["DC"].notnull(), season_mask_yr)
def test_fire_weather_ufunc_drystart(atmosds):
# This test is very shallow only tests if it runs.
ds = atmosds.assign(
tas=convert_units_to(atmosds.tas, "degC"),
pr=convert_units_to(atmosds.pr, "mm/d"),
)
season_mask_yr = fire_season(ds.tas, method="WF93", freq="YS")
out_ds = fire_weather_ufunc(
tas=ds.tas,
pr=ds.pr,
hurs=ds.hurs,
lat=ds.lat,
season_mask=season_mask_yr,
overwintering=False,
dry_start="CFS",
indexes=["DC", "DMC"],
dmc_dry_factor=5,
)
out_no = fire_weather_ufunc(
tas=ds.tas,
pr=ds.pr,
hurs=ds.hurs,
lat=ds.lat,
season_mask=season_mask_yr,
overwintering=False,
dry_start=None,
indexes=["DC", "DMC"],
)
# I know season of 1992 is a "wet" start.
xr.testing.assert_identical(
out_ds["DC"].sel(location="Montréal", time="1992"),
out_no["DC"].sel(location="Montréal", time="1992"),
)
xr.testing.assert_identical(
out_ds["DMC"].sel(location="Montréal", time="1992"),
out_no["DMC"].sel(location="Montréal", time="1992"),
)
def test_fire_weather_ufunc_errors(tas_series, pr_series, rh_series, ws_series):
tas = tas_series(np.ones(100), start="2017-01-01")
pr = pr_series(np.ones(100), start="2017-01-01")
rh = rh_series(np.ones(100), start="2017-01-01")
ws = ws_series(np.ones(100), start="2017-01-01")
snd = xr.full_like(tas, 0)
lat = xr.full_like(tas.isel(time=0), 45)
DC0 = xr.full_like(tas.isel(time=0), np.nan)
DMC0 = xr.full_like(tas.isel(time=0), np.nan)
FFMC0 = xr.full_like(tas.isel(time=0), np.nan)
# Test invalid combination
with pytest.raises(TypeError):
fire_weather_ufunc(
tas=tas,
pr=pr,
rh=rh,
ws=ws,
lat=lat,
dc0=DC0,
indexes=["DC", "ISI"],
)
# Test missing arguments
with pytest.raises(TypeError):
fire_weather_ufunc(
tas=tas,
pr=pr,
dc0=DC0,
indexes=["DC"], # lat=lat,
)
with pytest.raises(TypeError):
fire_weather_ufunc(
tas=tas,
pr=pr,
lat=lat,
dc0=DC0,
indexes=["DC"],
start_up_mode="snow_depth",
)
# Test starting too early
with pytest.raises(ValueError):
fire_weather_ufunc(
tas=tas,
pr=pr,
lat=lat,
dc0=DC0,
snd=snd,
indexes=["DC"],
start_date="2017-01-01",
start_up_mode="snow_depth",
)
# Test output is complete
out = fire_weather_ufunc(
tas=tas,
pr=pr,
lat=lat,
dc0=DC0,
indexes=["DC"],
start_date="2017-03-03",
)
assert len(out.keys()) == 1
out = fire_weather_ufunc(
tas=tas,
pr=pr,
rh=rh,
ws=ws,
lat=lat,
snd=snd,
dc0=DC0,
dmc0=DMC0,
ffmc0=FFMC0,
indexes=["DSR"],
start_date="2017-01-01",
)
assert len(out.keys()) == 7
def test_fire_weather_ufunc_errors(tas_series, pr_series, hurs_series,
sfcWind_series):
tas = tas_series(np.ones(100), start="2017-01-01")
pr = pr_series(np.ones(100), start="2017-01-01")
hurs = hurs_series(np.ones(100), start="2017-01-01")
sfcWind = sfcWind_series(np.ones(100), start="2017-01-01")
snd = xr.full_like(tas, 0)
lat = xr.full_like(tas.isel(time=0), 45)
DC0 = xr.full_like(tas.isel(time=0), np.nan) # noqa
DMC0 = xr.full_like(tas.isel(time=0), np.nan) # noqa
FFMC0 = xr.full_like(tas.isel(time=0), np.nan) # noqa
# Test invalid combination
with pytest.raises(TypeError):
fire_weather_ufunc(
tas=tas,
pr=pr,
hurs=hurs,
lat=lat,
dc0=DC0,
indexes=["DC", "ISI"],
)
# Test missing arguments
with pytest.raises(TypeError):
fire_weather_ufunc(
tas=tas,
pr=pr,
dc0=DC0,
indexes=["DC"], # lat=lat,
)
with pytest.raises(TypeError):
fire_weather_ufunc(
tas=tas,
pr=pr,
lat=lat,
dc0=DC0,
indexes=["DC"],
season_method="LA08",
)
# Test output is complete + dask
out = fire_weather_ufunc(
tas=tas.chunk(),
pr=pr.chunk(),
lat=lat.chunk(),
dc0=DC0,
indexes=["DC"],
)
assert len(out.keys()) == 1
out["DC"].load()
out = fire_weather_ufunc(
tas=tas,
pr=pr,
hurs=hurs,
sfcWind=sfcWind,
lat=lat,
snd=snd,
dc0=DC0,
dmc0=DMC0,
ffmc0=FFMC0,
indexes=["DSR"],
)
assert len(out.keys()) == 7
def drought_code(
tas: xarray.DataArray,
pr: xarray.DataArray,
lat: xarray.DataArray,
snd: xarray.DataArray = None,
dc0: xarray.DataArray = None,
start_date: str = None,
start_up_mode: str = None,
shut_down_mode: str = "snow_depth",
**params,
):
r"""The daily drought code (FWI component)
The drought code is part of the Canadian Forest Fire Weather Index System.
It is a numeric rating of the average moisture content of organic layers.
Parameters
----------
tas : xarray.DataArray
Noon temperature.
pr : xarray.DataArray
Rain fall in open over previous 24 hours, at noon.
lat : xarray.DataArray
Latitude coordinate
snd : xarray.DataArray
Noon snow depth.
dc0 : xarray.DataArray
Initial values of the drought code.
start_date : str, datetime.datetime
Date at which to start the computation, dc0/dmc0/ffcm0 should be given at the day before.
start_up_mode : {None, "snow_depth"}
How to compute start up. Mode "snow_depth" requires the additional "snd" array. See the FWI submodule doc for valid values.
shut_down_mode : {"temperature", "snow_depth"}
How to compute shut down. Mode "snow_depth" requires the additional "snd" array. See the FWI submodule doc for valid values.
params :
Any other keyword parameters as defined in `xclim.indices.fwi.fire_weather_ufunc`.
Returns
-------
Drought code [-]
Notes
-----
See https://cwfis.cfs.nrcan.gc.ca/background/dsm/fwi
References
----------
Y. Wang, K.R. Anderson, and R.M. Suddaby, INFORMATION REPORT NOR-X-424, 2015.
"""
tas = convert_units_to(tas, "C")
pr = convert_units_to(pr, "mm/day")
if snd is not None:
snd = convert_units_to(snd, "m")
if dc0 is None:
dc0 = xarray.full_like(tas.isel(time=0), np.nan)
params["start_date"] = start_date
params["start_up_mode"] = start_up_mode
out = fwi.fire_weather_ufunc(tas=tas,
pr=pr,
lat=lat,
dc0=dc0,
snd=snd,
indexes=["DC"],
**params)
return out["DC"]
def fire_weather_indexes(
tas: xarray.DataArray,
pr: xarray.DataArray,
ws: xarray.DataArray,
rh: xarray.DataArray,
lat: xarray.DataArray,
snd: xarray.DataArray = None,
ffmc0: xarray.DataArray = None,
dmc0: xarray.DataArray = None,
dc0: xarray.DataArray = None,
start_date: str = None,
**params,
):
r"""Return the six daily fire weather indexes.
Computes the 6 fire weather indexes as defined by the Canadian Forest Service:
the Drought Code, the Duff-Moisture Code, the Fine Fuel Moisture Code,
the Initial Spread Index, the Build Up Index and the Fire Weather Index.
Parameters
----------
tas : xarray.DataArray
Noon temperature.
pr : xarray.DataArray
Rain fall in open over previous 24 hours, at noon.
ws : xarray.DataArray
Noon wind speed.
rh : xarray.DataArray
Noon relative humidity.
lat : xarray.DataArray
Latitude coordinate
snd : xarray.DataArray
Noon snow depth.
ffmc0 : xarray.DataArray
Initial values of the fine fuel moisture code.
dmc0 : xarray.DataArray
Initial values of the Duff moisture code.
dc0 : xarray.DataArray
Initial values of the drought code.
start_date : str, datetime.datetime
Date at which to start the computation, dc0/dmc0/ffcm0 should be given at the day before.
params :
Any other keyword parameters as defined in `xclim.indices.fwi.fire_weather_ufunc`.
Returns
-------
DC, DMC, FFMC, ISI, BUI, FWI
Notes
-----
See https://cwfis.cfs.nrcan.gc.ca/background/dsm/fwi
References
----------
Y. Wang, K.R. Anderson, and R.M. Suddaby, INFORMATION REPORT NOR-X-424, 2015.
"""
tas = convert_units_to(tas, "C")
pr = convert_units_to(pr, "mm/day")
ws = convert_units_to(ws, "km/h")
rh = convert_units_to(rh, "pct")
if snd is not None:
snd = convert_units_to(snd, "m")
if dc0 is None:
dc0 = xarray.full_like(tas.isel(time=0), np.nan)
if dmc0 is None:
dmc0 = xarray.full_like(tas.isel(time=0), np.nan)
if ffmc0 is None:
ffmc0 = xarray.full_like(tas.isel(time=0), np.nan)
params["start_date"] = start_date
out = fwi.fire_weather_ufunc(
tas=tas,
pr=pr,
rh=rh,
ws=ws,
lat=lat,
dc0=dc0,
dmc0=dmc0,
ffmc0=ffmc0,
snd=snd,
indices=["DC", "DMC", "FFMC", "ISI", "BUI", "FWI"],
**params,
)
return out["DC"], out["DMC"], out["FFMC"], out["ISI"], out["BUI"], out[
"FWI"]