diff --git a/.claude/sweep-error-handling-state.csv b/.claude/sweep-error-handling-state.csv
new file mode 100644
index 000000000..c86df4360
--- /dev/null
+++ b/.claude/sweep-error-handling-state.csv
@@ -0,0 +1,2 @@
+module,last_inspected,issue,severity_max,categories_found,notes
+convolution,2026-07-02,,HIGH,1;2;3;4,"convolve_2d/convolution_2d skipped kernel + DataArray validation: None/1D/3D/list kernel -> numba TypingError, even kernel silently off-center (custom_kernel rejects it), numpy agg -> memoryview astype error. Fixed via _validate_kernel + _validate_raster; branch deep-sweep-error-handling-convolution-2026-07-02 pushed to fork; issue/PR create blocked by auto-mode, open from parent. MEDIUM(unfixed): annulus_kernel inner>outer -> cryptic np.pad 'index cant contain negative values'. LOW: circle_kernel cellsize=0 ZeroDivisionError, cellsize<0 cryptic linspace; calc_cellsize non-DataArray -> AttributeError attrs. cupy verified."
diff --git a/xrspatial/convolution.py b/xrspatial/convolution.py
index b1b08bfb7..f185d56b1 100644
--- a/xrspatial/convolution.py
+++ b/xrspatial/convolution.py
@@ -344,6 +344,34 @@ def custom_kernel(kernel):
     return kernel
 
 
+def _validate_kernel(kernel, func_name='convolve_2d'):
+    """Validate a convolution kernel: a 2D array with odd side lengths.
+
+    Duck-typed on ``ndim``/``shape`` so numpy and cupy kernels both pass.
+    Rejects up front so a malformed kernel raises a clear ValueError
+    instead of an inscrutable numba ``TypingError`` (or silent off-center
+    output for even side lengths). Mirrors ``custom_kernel``'s odd-shape
+    contract.
+    """
+    if not hasattr(kernel, 'ndim') or not hasattr(kernel, 'shape'):
+        raise ValueError(
+            f"{func_name}(): `kernel` must be a 2D array with odd side "
+            f"lengths, got {type(kernel).__module__}."
+            f"{type(kernel).__qualname__}"
+        )
+    if kernel.ndim != 2:
+        raise ValueError(
+            f"{func_name}(): `kernel` must be a 2D array, got {kernel.ndim}D "
+            f"with shape {tuple(kernel.shape)}"
+        )
+    rows, cols = kernel.shape
+    if rows % 2 == 0 or cols % 2 == 0:
+        raise ValueError(
+            f"{func_name}(): `kernel` must have odd side lengths so it has a "
+            f"well-defined center, got shape {(rows, cols)}"
+        )
+
+
 @jit(nopython=True, nogil=True)
 def _convolve_2d_numpy(data, kernel):
     # apply kernel to data image.
@@ -483,6 +511,7 @@ def convolve_2d(data, kernel, boundary='nan'):
     agg = xr.DataArray(data)
     _validate_raster(agg, func_name='convolve_2d', ndim=2)
     _validate_boundary(boundary)
+    _validate_kernel(kernel, func_name='convolve_2d')
     mapper = ArrayTypeFunctionMapping(
         numpy_func=_convolve_2d_numpy_boundary,
         cupy_func=_convolve_2d_cupy,
@@ -615,6 +644,7 @@ def convolution_2d(agg, kernel, name='convolution_2d', boundary='nan'):
     """
 
     # wrapper of convolve_2d
+    _validate_raster(agg, func_name='convolution_2d', ndim=2)
     out = convolve_2d(agg.data, kernel, boundary)
     return xr.DataArray(out,
                         name=name,
diff --git a/xrspatial/tests/test_convolution.py b/xrspatial/tests/test_convolution.py
index dff4af4a7..1ce72bd03 100644
--- a/xrspatial/tests/test_convolution.py
+++ b/xrspatial/tests/test_convolution.py
@@ -2,7 +2,9 @@
 import pytest
 import xarray as xr
 
-from xrspatial.convolution import circle_kernel, convolve_2d, custom_kernel
+from xrspatial.convolution import (
+    circle_kernel, convolution_2d, convolve_2d, custom_kernel,
+)
 
 
 KERNEL = circle_kernel(1, 1, 1)
@@ -48,3 +50,48 @@ def test_convolve_2d_accepts_float64():
     # Centre cell is finite; edges are NaN by default boundary mode.
     assert np.isfinite(out[2, 2])
     assert np.isnan(out[0, 0])
+
+
+DATA = np.arange(25, dtype=np.float64).reshape(5, 5)
+
+
+@pytest.mark.parametrize("bad_kernel", [
+    None,
+    np.ones(3, dtype=np.float64),            # 1D
+    np.ones((3, 3, 3), dtype=np.float64),    # 3D
+    [[0, 1, 0], [1, 1, 1], [0, 1, 0]],       # python list, not an array
+])
+def test_convolve_2d_rejects_bad_kernel(bad_kernel):
+    # Bad kernels used to crash deep in numba with a cryptic TypingError.
+    # convolve_2d must reject them up front with a clear message that names
+    # `kernel`.
+    with pytest.raises(ValueError, match="kernel"):
+        convolve_2d(DATA, bad_kernel)
+
+
+@pytest.mark.parametrize("even_kernel", [
+    np.ones((2, 2), dtype=np.float64),
+    np.ones((4, 4), dtype=np.float64),
+    np.ones((2, 3), dtype=np.float64),
+])
+def test_convolve_2d_rejects_even_kernel(even_kernel):
+    # An even side length has no well-defined center; convolve_2d used to
+    # silently produce an off-center result. custom_kernel already rejects
+    # even kernels, so convolve_2d must too.
+    with pytest.raises(ValueError, match="odd"):
+        convolve_2d(DATA, even_kernel)
+
+
+def test_convolution_2d_rejects_non_dataarray():
+    # Passing a plain numpy array used to fail with an inscrutable
+    # "'memoryview' object has no attribute 'astype'"; validate up front.
+    with pytest.raises(TypeError, match="DataArray"):
+        convolution_2d(DATA, KERNEL)
+
+
+def test_convolution_2d_accepts_dataarray():
+    # Positive path unchanged.
+    agg = xr.DataArray(DATA, dims=['y', 'x'])
+    out = convolution_2d(agg, KERNEL)
+    assert isinstance(out, xr.DataArray)
+    assert out.shape == agg.shape