return number of days, add indicator and translation, add tests

Signed-off-by: Trevor James Smith <10819524+Zeitsperre@users.noreply.github.com>

.github/workflows/main.yml

@@ -19,7 +19,7 @@ on:
       - submitted
 
 env:
-  XCLIM_TESTDATA_BRANCH: v2024.8.23
+  XCLIM_TESTDATA_BRANCH: add-snw-prsn
 
 concurrency:
   # For a given workflow, if we push to the same branch, cancel all previous builds on that branch except on main.

src/xclim/data/fr.json

@@ -1033,6 +1033,18 @@
     "title": "Jours avec neige",
     "abstract": "Nombre de jours où la neige est entre une borne inférieure et supérieure."
   },
+  "HOLIDAY_SNOW_DAYS": {
+    "long_name": "Nombre de jours de neige durant les jours fériés",
+    "description": "Nombre de jours de neige durant les jours fériés.",
+    "title": "Jours de neige durant les jours fériés",
+    "abstract": "Nombre de jours de neige durant les jours fériés."
+  },
+  "HOLIDAY_SNOW_AND_SNOWFALL_DAYS": {
+    "long_name": "Nombre de jours de neige et de jours de chute de neige durant les jours fériés",
+    "description": "Nombre de jours de neige et de jours de chute de neige durant les jours fériés.",
+    "title": "Jours de neige et de chute de neige durant les jours fériés",
+    "abstract": "Nombre de jours de neige et de jours de chute de neige durant les jours fériés."
+  },
   "SND_SEASON_LENGTH": {
     "long_name": "Durée de couvert de neige",
     "description": "La saison débute lorsque l'épaisseur de neige est au-dessus de {thresh} durant {window} jours et se termine lorsqu'elle redescend sous {thresh} durant {window} jours.",

src/xclim/indicators/land/_snow.py

@@ -8,6 +8,8 @@
 
 __all__ = [
     "blowing_snow",
+    "holiday_snow_and_snowfall_days",
+    "holiday_snow_days",
     "snd_days_above",
     "snd_max_doy",
     "snd_season_end",
@@ -254,3 +256,26 @@ class SnowWithIndexing(ResamplingIndicatorWithIndexing):
     abstract="Number of days when the snow amount is greater than or equal to a given threshold.",
     compute=xci.snw_days_above,
 )
+
+holiday_snow_days = Snow(
+    title="Christmas snow days",
+    identifier="holiday_snow_days",
+    units="1",
+    long_name="Number of holiday days with snow",
+    description="The total number of days where snow on the ground was greater than or equal to {snd_thresh} "
+    "occurring on {date_start} and ending on {date_end}.",
+    abstract="The total number of days where there is a significant amount of snow on the ground on December 25th.",
+    compute=xci.holiday_snow_days,
+)
+
+holiday_snow_and_snowfall_days = Snow(
+    title="Perfect Christmas snow days",
+    identifier="holiday_snow_and_snowfall_days",
+    units="1",
+    long_name="Number of holiday days with snow and snowfall",
+    description="The total number of days where snow on the ground was greater than or equal to {snd_thresh} "
+    "and snowfall was greater than or equal to {prsn_thresh} occurring on {date_start} and ending on {date_end}.",
+    abstract="The total number of days where there is a significant amount of snow on the ground "
+    "and a measurable snowfall occurring on December 25th.",
+    compute=xci.holiday_snow_and_snowfall_days,
+)

src/xclim/indices/_threshold.py

@@ -3680,8 +3680,8 @@ def holiday_snow_days(
     ----------
     https://www.canada.ca/en/environment-climate-change/services/weather-general-tools-resources/historical-christmas-snowfall-data.html
     """
-    snow_depth = convert_units_to(snd, "mm", context="hydro")
-    snow_depth_thresh = convert_units_to(snd_thresh, "mm", context="hydro")
+    snow_depth = convert_units_to(snd, "m")
+    snow_depth_thresh = convert_units_to(snd_thresh, "m")
     snow_depth_constrained = select_time(
         snow_depth,
         drop=True,
@@ -3691,7 +3691,7 @@ def holiday_snow_days(
     xmas_days = (
         (snow_depth_constrained >= snow_depth_thresh)
         .resample(time=freq)
-        .map(lambda x: x.all(dim="time"))
+        .map(lambda x: x.sum(dim="time"))
     )
 
     xmas_days = xmas_days.assign_attrs({"units": "1"})
@@ -3708,7 +3708,7 @@ def holiday_snow_and_snowfall_days(
     snd: xarray.DataArray,
     prsn: xarray.DataArray | None = None,
     snd_thresh: Quantified = "20 mm",
-    prsn_thresh: Quantified = "1 mm",
+    prsn_thresh: Quantified = "1 cm",
     date_start: str = "12-25",
     date_end: str | None = None,
     freq: str = "YS-JUL",
@@ -3739,15 +3739,23 @@ def holiday_snow_and_snowfall_days(
 
     Returns
     -------
-    xarray.DataArray, [bool]
-        Boolean array of years with Perfect Christmas Days.
+    xarray.DataArray, [int]
+        The total number of days with snow and snowfall during the holiday.
 
     References
     ----------
     https://www.canada.ca/en/environment-climate-change/services/weather-general-tools-resources/historical-christmas-snowfall-data.html
     """
+    snow_depth = convert_units_to(snd, "m")
+    snow_depth_thresh = convert_units_to(snd_thresh, "m")
+    snow_depth_constrained = select_time(
+        snow_depth,
+        drop=True,
+        date_bounds=(date_start, date_start if date_end is None else date_end),
+    )
+
     snowfall_rate = rate2amount(
-        convert_units_to(prsn, "mm/d", context="hydro"), out_units="mm"
+        convert_units_to(prsn, "mm day-1", context="hydro"), out_units="mm"
     )
     snowfall_thresh = convert_units_to(prsn_thresh, "mm", context="hydro")
     snowfall_constrained = select_time(
@@ -3756,21 +3764,13 @@ def holiday_snow_and_snowfall_days(
         date_bounds=(date_start, date_start if date_end is None else date_end),
     )
 
-    snow_depth = convert_units_to(snd, "mm", context="hydro")
-    snow_depth_thresh = convert_units_to(snd_thresh, "mm", context="hydro")
-    snow_depth_constrained = select_time(
-        snow_depth,
-        drop=True,
-        date_bounds=(date_start, date_start if date_end is None else date_end),
-    )
-
     perfect_xmas_days = (
         (
             (snow_depth_constrained >= snow_depth_thresh)
             & (snowfall_constrained >= snowfall_thresh)
         )
         .resample(time=freq)
-        .map(lambda x: x.all(dim="time"))
+        .map(lambda x: x.sum(dim="time"))
     )
 
     perfect_xmas_days = perfect_xmas_days.assign_attrs({"units": "1"})

tests/test_indices.py

@@ -1468,6 +1468,64 @@ def test_1d(
         np.testing.assert_allclose(hwml.values, expected)
 
 
+class TestHolidayIndices:
+
+    def test_xmas_days_simple(self, snd_series):
+        # 5ish years of data
+        snd = snd_series(np.zeros(365 * 5), units="cm")
+
+        # add snow on ground on December 25 for first 3 years
+        snd.loc["2000-12-25"] = 2
+        snd.loc["2001-12-25"] = 1.5  # not enough
+        snd.loc["2002-12-25"] = 2
+        snd.loc["2003-12-25"] = 0  # no snow
+        snd.loc["2004-12-25"] = 6
+
+        out = xci.holiday_snow_days(snd)
+        np.testing.assert_array_equal(out, [1, 0, 1, 0, 1])
+
+    def test_xmas_days_range(self, snd_series):
+        # 5ish years of data
+        snd = snd_series(np.zeros(365 * 5), units="cm")
+
+        # add snow on ground on December 25 for first 3 years
+        snd.loc["2000-12-25"] = 2
+        snd.loc["2001-12-25"] = 1.5  # not enough
+        snd.loc["2002-12-24"] = 10  # a réveillon miracle
+        snd.loc["2002-12-25"] = 2
+        snd.loc["2003-12-25"] = 0  # no snow
+        snd.loc["2004-12-25"] = 6
+
+        out = xci.holiday_snow_days(snd, date_start="12-24", date_end="12-25")
+        np.testing.assert_array_equal(out, [1, 0, 2, 0, 1])
+
+    def test_perfect_xmas_days_simple(self, snd_series, prsn_series):
+        # 5ish years of data
+        a = np.zeros(365 * 5)
+        snd = snd_series(a, units="mm")
+        prsn = prsn_series(a.copy(), units="cm day-1")
+
+        # add snow on ground on December 25
+        snd.loc["2000-12-25"] = 20
+        snd.loc["2001-12-25"] = 15  # not enough
+        snd.loc["2001-12-26"] = 30  # too bad it's Boxing Day
+        snd.loc["2002-12-25"] = 20
+        snd.loc["2003-12-25"] = 0  # no snow
+        snd.loc["2004-12-25"] = 60
+
+        # add snowfall on December 25
+        prsn.loc["2000-12-25"] = 5
+        prsn.loc["2001-12-25"] = 2
+        prsn.loc["2001-12-26"] = 30  # too bad it's Boxing Day
+        prsn.loc["2002-12-25"] = 0.5  # not quite enough
+        prsn.loc["2003-12-25"] = 0  # no snow
+        prsn.loc["2004-12-25"] = 10
+        prsn = convert_units_to(prsn, "kg m-2 s-1", context="hydro")
+
+        out = xci.holiday_snow_and_snowfall_days(snd, prsn)
+        np.testing.assert_array_equal(out, [1, 0, 0, 0, 1])
+
+
 class TestHotSpellFrequency:
     @pytest.mark.parametrize(
         "thresh,window,op,expected",