diff --git a/pyproject.toml b/pyproject.toml
index 25cbcdad0..3c5647cab 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -37,6 +37,7 @@ classifiers = [
 test = [
     # "pandas>=3.0,<4.0",
     "pytest>=9.0,<10.0",
+    "pytest-env>=1.0,<2.0",
     "coverage>=7.6.1,<8.0",
 ]
 lint = [
@@ -62,10 +63,9 @@ gui = [
 [tool.pytest.ini_options]
 # pythonpath = [".", "python/rateslib"]
 minversion = "8.0"
-addopts = """
-   --ignore-glob=*_ignore.py
-   --override-ini='env=MPLBACKEND=Agg'
-"""  # use -s to show print capture, use -q for quiet, use -v for verbose
+addopts = [
+   "--ignore-glob=*_ignore.py",
+] # use -s to show print capture, use -q for quiet, use -v for verbose
 testpaths = [
     "python/tests",
 ]
@@ -74,6 +74,9 @@ filterwarnings = [
     "ignore::PendingDeprecationWarning"
 ]
 
+[tool.pytest_env]
+MPLBACKEND = "Agg"
+
 [tool.setuptools]
 packages = ["rateslib"]
 
diff --git a/python/rateslib/volatility/ir/base.py b/python/rateslib/volatility/ir/base.py
index b9423eedc..fd206ccee 100644
--- a/python/rateslib/volatility/ir/base.py
+++ b/python/rateslib/volatility/ir/base.py
@@ -674,6 +674,14 @@ def _construct_smile(
         tenor: datetime,
         params: Sequence[DualTypes] | Arr1dObj,
     ) -> _BaseIRSmile:
+        if isinstance(self.meta.time_scalars, NoInput):
+            ts = NoInput(0)
+        else:
+            if expiry > self.meta.time_scalars.index[-1]:
+                ts = NoInput(0)
+            else:
+                ts = self.meta.time_scalars[expiry]
+
         return self._SmileType(  # type: ignore[call-arg]
             nodes=dict(zip(self.meta.indexes, params, strict=True)),
             eval_date=self.meta.eval_date,
@@ -682,6 +690,7 @@ def _construct_smile(
             tenor=tenor,
             shift=self.meta.shift,
             ad=None,  # inherit the AD variables from the params
+            time_scalar=ts,
             **self.meta.smile_params,
         )
 
diff --git a/python/rateslib/volatility/ir/utils.py b/python/rateslib/volatility/ir/utils.py
index 823c3f59f..cb423fedd 100644
--- a/python/rateslib/volatility/ir/utils.py
+++ b/python/rateslib/volatility/ir/utils.py
@@ -20,6 +20,7 @@
 import numpy as np
 from pandas import Series
 
+from rateslib import calendars
 from rateslib.data.fixings import IRSFixing, _get_irs_series
 from rateslib.enums.generics import NoInput
 from rateslib.scheduling import Adjuster, add_tenor
@@ -212,6 +213,16 @@ def __post_init__(self) -> None:
         for idx in range(1, len(self.expiries)):
             if self.expiry_dates[idx - 1] >= self.expiry_dates[idx]:
                 raise ValueError("Cube `expiries` are not sorted or contain duplicates.\n")
+        if not isinstance(self._weights, NoInput):
+            object.__setattr__(
+                self,
+                "_weights",
+                _scale_weights(
+                    eval_date=self.eval_date,
+                    weights=self._weights,
+                    expiries=self.expiry_dates,
+                ),
+            )
 
     @property
     def shift(self) -> DualTypes:
@@ -252,13 +263,15 @@ def weights(self) -> Series[float] | NoInput:
         return self._weights
 
     @cached_property
-    def weights_cum(self) -> Series[float] | NoInput:
+    def time_scalars(self) -> Series[float] | NoInput:
         """Weight adjusted time to expiry (in calendar days) per date for temporal volatility
         interpolation."""
         if isinstance(self.weights, NoInput):
-            return self.weights
+            return NoInput(0)
         else:
-            return self.weights.cumsum()
+            c = Series(index=self.weights.index, data=1.0)
+            c.iloc[0] = 0.0
+            return self.weights.cumsum() / c.cumsum()
 
     @property
     def tenors(self) -> list[str]:
@@ -506,3 +519,55 @@ def _bilinear_interp(
         + bl * (1 - h[1]) * v[0]
         + br * h[1] * v[1]
     )
+
+
+def _scale_weights(
+    eval_date: datetime,
+    weights: Series[float],
+    expiries: list[datetime],
+) -> Series[float]:
+    # the last weight is considered the end point of interest
+    w = weights.sort_index(ascending=True)  # sorted input
+    del weights
+    d = calendars.get("all").cal_date_range(eval_date, w.index[-1])
+    s = Series(data=1.0, index=d)
+    s.update(w)
+    s.update(Series(index=[eval_date], data=0.0))
+    c = s.cumsum()
+    adj_expiries = [eval_date] + expiries
+    for i, expiry in enumerate(adj_expiries):
+        if i == 0:
+            continue
+        if expiry < s.index[-1]:
+            # this expiry is within the middle of the weights series
+            left_index = (adj_expiries[i - 1] - eval_date).days
+            right_index = (expiry - adj_expiries[i - 1]).days + left_index
+            left_count = c[adj_expiries[i - 1]]
+            right_count = c[adj_expiries[i]]
+            s.iloc[left_index + 1 : right_index + 1] *= (right_index - left_index) / (
+                right_count - left_count
+            )
+        elif adj_expiries[i - 1] < s.index[-1]:
+            # the weights extend beyond the last expiry but to to the present expiry
+            left_index = (adj_expiries[i - 1] - eval_date).days
+            right_index = (s.index[-1] - adj_expiries[i - 1]).days + left_index
+            left_count = c[adj_expiries[i - 1]]
+            right_count = c[s.index[-1]]
+            s.iloc[left_index + 1 : right_index + 1] *= (right_index - left_index) / (
+                right_count - left_count
+            )
+        else:
+            # the weights have been exhausted
+            break
+
+    if s.index[-1] > expiries[-1]:
+        # scale the weights beyond last expiry
+        left_index = (adj_expiries[-1] - eval_date).days
+        right_index = (s.index[-1] - adj_expiries[-1]).days + left_index
+        left_count = c[adj_expiries[-1]]
+        right_count = c[s.index[-1]]
+        s.iloc[left_index + 1 : right_index + 1] *= (right_index - left_index) / (
+            right_count - left_count
+        )
+
+    return s
diff --git a/python/tests/test_ir_volatility.py b/python/tests/test_ir_volatility.py
index 94007a186..42fbed677 100644
--- a/python/tests/test_ir_volatility.py
+++ b/python/tests/test_ir_volatility.py
@@ -18,7 +18,7 @@
 from matplotlib import pyplot as plt
 from pandas import DataFrame, Index, IndexSlice, Series
 from pandas.testing import assert_frame_equal, assert_series_equal
-from rateslib import default_context
+from rateslib import calendars, default_context
 from rateslib.curves import CompositeCurve, Curve, LineCurve
 from rateslib.data.fixings import IRSSeries
 from rateslib.default import NoInput
@@ -32,7 +32,7 @@
     IRSplineCube,
     IRSplineSmile,
 )
-from rateslib.volatility.ir.utils import _bilinear_interp
+from rateslib.volatility.ir.utils import _bilinear_interp, _scale_weights
 from rateslib.volatility.utils import _OptionModelBachelier, _OptionModelBlack76, _SabrSmileNodes
 
 
@@ -1523,6 +1523,66 @@ def test_set_node_vector(self):
         assert result[2] == Dual(0.30, ["X_a_1_0"], [])
         assert result[9] == Dual(20.0, ["X_v_0_1"], [])
 
+    @pytest.mark.parametrize(
+        ("weights", "expiries"),
+        [
+            (
+                Series(index=[dt(2000, 1, 3), dt(2000, 1, 8), dt(2000, 1, 4)], data=0.0),
+                [dt(2000, 1, 5), dt(2000, 1, 10), dt(2000, 1, 15)],
+            ),
+            (
+                Series(index=[dt(2000, 1, 3), dt(2000, 1, 20), dt(2000, 1, 4)], data=0.0),
+                [dt(2000, 1, 5), dt(2000, 1, 10), dt(2000, 1, 15)],
+            ),
+        ],
+    )
+    def test_weights_implementation(self, weights, expiries):
+        result = _scale_weights(
+            eval_date=dt(2000, 1, 1),
+            weights=weights,
+            expiries=expiries,
+        )
+
+        c = result.cumsum()
+        for expiry in expiries:
+            if expiry > c.index[-1]:
+                assert c.iloc[-1] == (c.index[-1] - dt(2000, 1, 1)).days
+            else:
+                assert c[expiry] == (expiry - dt(2000, 1, 1)).days
+
+        assert c.iloc[-1] == (c.index[-1] - dt(2000, 1, 1)).days
+
+    def test_weights(self):
+        nyc = calendars.get("nyc")
+        irsc = IRSabrCube(
+            eval_date=dt(2000, 1, 1),
+            expiries=["1y", "2y"],
+            tenors=["1y", "2y"],
+            irs_series=IRSSeries(
+                currency="usd",
+                settle=0,
+                frequency="A",
+                convention="Act360",
+                calendar="all",
+                leg2_fixing_method="ibor(2)",
+            ),
+            beta=0.5,
+            alpha=np.array([[0.1, 0.2], [0.3, 0.4]]),
+            rho=np.array([[1.0, 2.0], [3.0, 4.0]]),
+            nu=np.array([[10.0, 20.0], [30.0, 40.0]]),
+            id="X",
+            weights=Series(
+                index=[
+                    _
+                    for _ in nyc.cal_date_range(dt(2000, 1, 1), dt(2001, 2, 3))
+                    if nyc.is_non_bus_day(_)
+                ],
+                data=0.0,
+            ),
+        )
+        result = irsc.meta.time_scalars
+        assert abs(result.iloc[-1] - 1.0) < 1e-14
+
 
 class TestIRSplineSmile:
     @pytest.mark.parametrize(
@@ -1998,6 +2058,73 @@ def test_pricing_model(self, model, metric):
         expected = 20.0
         assert abs(result - expected) < 1e-6
 
+    def test_business_day_time_and_weights(self):
+        nyc = calendars.get("nyc")
+        irsc = IRSplineCube(
+            eval_date=dt(2000, 1, 3),
+            expiries=["1m", "3m", "6m"],
+            tenors=["1y"],
+            strikes=[0],
+            parameters=[[[30.0]], [[35.0]], [[38.0]]],
+            irs_series="usd_irs",
+        )
+        irsc2 = IRSplineCube(
+            eval_date=dt(2000, 1, 3),
+            expiries=["1m", "3m", "6m"],
+            tenors=["1y"],
+            strikes=[0],
+            parameters=[[[30.0]], [[35.0]], [[38.0]]],
+            irs_series="usd_irs",
+            weights=Series(
+                index=[
+                    _
+                    for _ in nyc.cal_date_range(dt(2000, 1, 7), dt(2000, 7, 15))
+                    if nyc.is_non_bus_day(_)
+                ],
+                data=0.0,
+            ),
+        )
+        curve = Curve(
+            nodes={dt(2000, 1, 3): 1.0, dt(2002, 1, 3): 0.93},
+            convention="act360",
+            calendar="nyc",
+        )
+        for expiry in irsc.meta.expiry_dates:
+            # test at expiries time remapping does not exist because these are the natural pillars
+            iro = IRSCall(
+                expiry=expiry,
+                strike="atm",
+                irs_series="usd_irs",
+                tenor="1y",
+            )
+            r1 = iro.rate(curves=curve, vol=irsc, metric="percentnotional") * 100.0
+            r2 = iro.rate(curves=curve, vol=irsc2, metric="percentnotional") * 100.0
+            assert abs(r1 - r2) < 1e-8
+
+        for expiry in [dt(2000, 1, 14), dt(2000, 2, 18), dt(2000, 5, 12)]:
+            # test at expiries inbetween the time remapping exists
+            iro = IRSCall(
+                expiry=expiry,
+                strike="atm",
+                irs_series="usd_irs",
+                tenor="1y",
+            )
+            r1 = iro.rate(curves=curve, vol=irsc, metric="percentnotional") * 100.0
+            r2 = iro.rate(curves=curve, vol=irsc2, metric="percentnotional") * 100.0
+            assert abs(r1 - r2) > 1e-3
+
+        for expiry in [dt(2000, 7, 20), dt(2000, 7, 25)]:
+            # test after weights stop being defined
+            iro = IRSCall(
+                expiry=expiry,
+                strike="atm",
+                irs_series="usd_irs",
+                tenor="1y",
+            )
+            r1 = iro.rate(curves=curve, vol=irsc, metric="percentnotional") * 100.0
+            r2 = iro.rate(curves=curve, vol=irsc2, metric="percentnotional") * 100.0
+            assert abs(r1 - r2) < 1e-8
+
 
 class TestStateAndCache:
     @pytest.mark.parametrize(