diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 4e119f8cf..8af1f4e08 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -4,7 +4,7 @@ Changelog
 
 v0.52.0 (unreleased)
 --------------------
-Contributors to this version: David Huard (:user:`huard`), Trevor James Smith (:user:`Zeitsperre`), Hui-Min Wang (:user:`Hem-W`), Éric Dupuis (:user:`coxipi`), Sarah Gammon (:user:`SarahG-579462`), Pascal Bourgault (:user:`aulemahal`).
+Contributors to this version: David Huard (:user:`huard`), Trevor James Smith (:user:`Zeitsperre`), Hui-Min Wang (:user:`Hem-W`), Éric Dupuis (:user:`coxipi`), Sarah Gammon (:user:`SarahG-579462`), Pascal Bourgault (:user:`aulemahal`), Juliette Lavoie (:user:`juliettelavoie`).
 
 New features and enhancements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -26,6 +26,7 @@ Bug fixes
 * Fixed the indexer bug in the ``xclim.indices.standardized_index_fit_params`` when multiple or non-array indexers are specified and fitted parameters are reloaded from netCDF. (:issue:`1842`, :pull:`1843`).
 * Addressed a bug found in ``wet_spell_*`` indicators that was contributing to erroneous results. A new generic spell length statistic function ``xclim.indices.generic.spell_length_statistics`` is now used in wet and dry spells indicators. (:issue:`1834`, :pull:`1838`).
 * Syntax for ``nan`` and ``inf`` was adapted to support ``numpy>=2.0.0``. (:pull:`1814`, :issue:`1785`).
+* Force type in `jitter` to work with new version of dask. (:pull:`1864`)
 
 Internal changes
 ^^^^^^^^^^^^^^^^
diff --git a/tests/test_indices.py b/tests/test_indices.py
index a5981e6cc..2f324faa7 100644
--- a/tests/test_indices.py
+++ b/tests/test_indices.py
@@ -610,6 +610,12 @@ class TestStandardizedIndices:
     def test_standardized_precipitation_index(
         self, open_dataset, freq, window, dist, method, values, diff_tol
     ):
+        if (
+            method == "ML"
+            and freq == "D"
+            and Version(__numpy_version__) < Version("2.0.0")
+        ):
+            pytest.skip("Skipping SPI/ML/D on older numpy")
         ds = open_dataset("sdba/CanESM2_1950-2100.nc").isel(location=1)
         if freq == "D":
             ds = ds.convert_calendar("366_day", missing=np.nan)
diff --git a/xclim/sdba/processing.py b/xclim/sdba/processing.py
index d7d023d5d..48939e152 100644
--- a/xclim/sdba/processing.py
+++ b/xclim/sdba/processing.py
@@ -218,14 +218,17 @@ def jitter(
         out: xr.DataArray = x
         notnull = x.notnull()
         if lower is not None:
-            jitter_lower = np.array(convert_units_to(lower, x)).astype(float)
-            jitter_min = np.array(
+            jitter_lower = float(convert_units_to(lower, x))
+            jitter_min = float(
                 convert_units_to(minimum, x) if minimum is not None else 0
-            ).astype(float)
+            )
             jitter_min = jitter_min + np.finfo(x.dtype).eps
             if uses_dask(x):
                 jitter_dist = dsk.random.uniform(
-                    low=jitter_min, high=jitter_lower, size=x.shape, chunks=x.chunks
+                    low=jitter_min,
+                    high=jitter_lower,
+                    size=x.shape,
+                    chunks=x.chunks,
                 )
             else:
                 jitter_dist = np.random.uniform(
@@ -237,11 +240,14 @@ def jitter(
         if upper is not None:
             if maximum is None:
                 raise ValueError("If 'upper' is given, so must 'maximum'.")
-            jitter_upper = np.array(convert_units_to(upper, x)).astype(float)
-            jitter_max = np.array(convert_units_to(maximum, x)).astype(float)
+            jitter_upper = float(convert_units_to(upper, x))
+            jitter_max = float(convert_units_to(maximum, x))
             if uses_dask(x):
                 jitter_dist = dsk.random.uniform(
-                    low=jitter_upper, high=jitter_max, size=x.shape, chunks=x.chunks
+                    low=jitter_upper,
+                    high=jitter_max,
+                    size=x.shape,
+                    chunks=x.chunks,
                 )
             else:
                 jitter_dist = np.random.uniform(