diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 6d44194f38f..c5e9d895c3b 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -407,6 +407,11 @@ Bug Fixes
 
 Documentation
 ~~~~~~~~~~~~~
+- Document how :py:meth:`Dataset.interp` and :py:meth:`DataArray.interp` handle
+  chunks of Dask arrays, and that loading chunked new coordinates first can
+  reduce the memory use for ``method="linear"`` and ``"nearest"``
+  (:pull:`11786`).
+  By `Michael Niklas <https://github.com/headtr1ck>`_.
 - Clarified that :py:meth:`DataArray.item` and :py:meth:`Variable.item` are not
   implemented for lazy (e.g. dask) arrays, both in the method docstring and in the
   raised error message, which now suggests loading the data into memory first
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index f0912ef7c1e..c978a23b5e3 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -2429,6 +2429,12 @@ def interp(
         - When interpolating along multiple dimensions with methods `linear` and `nearest`,
             the process attempts to decompose the interpolation into independent interpolations
             along one dimension at a time.
+        - For Dask arrays, the chunks along the interpolated dimensions are merged
+            into a single chunk. With methods `linear` and `nearest`, the data is
+            first subset to the range of the new coordinates, so only the chunks that
+            are needed are read. This only happens if the new coordinates are in
+            memory, so loading chunked new coordinates first (e.g. with ``.compute()``)
+            can reduce the memory use considerably if they are cheap to compute.
         - The specific interpolation method and dimensionality determine which
             interpolant is used:
 
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index e49ca858a81..b1f241bcb52 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -3895,6 +3895,12 @@ def interp(
         - When interpolating along multiple dimensions with methods `linear` and `nearest`,
             the process attempts to decompose the interpolation into independent interpolations
             along one dimension at a time.
+        - For Dask arrays, the chunks along the interpolated dimensions are merged
+            into a single chunk. With methods `linear` and `nearest`, the data is
+            first subset to the range of the new coordinates, so only the chunks that
+            are needed are read. This only happens if the new coordinates are in
+            memory, so loading chunked new coordinates first (e.g. with ``.compute()``)
+            can reduce the memory use considerably if they are cheap to compute.
         - The specific interpolation method and dimensionality determine which
             interpolant is used: