diff --git a/pandas/_libs/tslibs/conversion.pyx b/pandas/_libs/tslibs/conversion.pyx
index bf5429c39e8fe..67c2793e4bcef 100644
--- a/pandas/_libs/tslibs/conversion.pyx
+++ b/pandas/_libs/tslibs/conversion.pyx
@@ -4,7 +4,7 @@ from cython import Py_ssize_t
 
 import numpy as np
 cimport numpy as cnp
-from numpy cimport int64_t, int32_t, ndarray
+from numpy cimport uint8_t, int64_t, int32_t, ndarray
 cnp.import_array()
 
 import pytz
@@ -535,6 +535,7 @@ cdef inline void localize_tso(_TSObject obj, tzinfo tz):
         int64_t[:] deltas
         int64_t local_val
         Py_ssize_t pos
+        str typ
 
     assert obj.tzinfo is None
 
@@ -646,7 +647,7 @@ cdef inline int64_t[:] _tz_convert_dst(int64_t[:] values, tzinfo tz,
     if not is_tzlocal(tz):
         # get_dst_info cannot extract offsets from tzlocal because its
         # dependent on a datetime
-        trans, deltas, typ = get_dst_info(tz)
+        trans, deltas, _ = get_dst_info(tz)
         if not to_utc:
             # We add `offset` below instead of subtracting it
             deltas = -1 * np.array(deltas, dtype='i8')
@@ -690,7 +691,7 @@ cdef inline int64_t _tz_convert_tzlocal_utc(int64_t val, tzinfo tz,
     """
     cdef:
         npy_datetimestruct dts
-        int64_t result, delta
+        int64_t delta
         datetime dt
 
     dt64_to_dtstruct(val, &dts)
@@ -879,18 +880,20 @@ def tz_localize_to_utc(ndarray[int64_t] vals, object tz, object ambiguous=None,
     localized : ndarray[int64_t]
     """
     cdef:
-        ndarray[int64_t] trans
         int64_t[:] deltas, idx_shifted, idx_shifted_left, idx_shifted_right
-        ndarray ambiguous_array
+        ndarray[uint8_t, cast=True] ambiguous_array, both_nat, both_eq
         Py_ssize_t i, idx, pos, ntrans, n = len(vals)
         Py_ssize_t delta_idx_offset, delta_idx, pos_left, pos_right
         int64_t *tdata
         int64_t v, left, right, val, v_left, v_right, new_local, remaining_mins
         int64_t HOURS_NS = HOUR_SECONDS * 1000000000
-        ndarray[int64_t] result, result_a, result_b, dst_hours
+        ndarray[int64_t] trans, result, result_a, result_b, dst_hours
+        ndarray[int64_t] trans_idx, grp, delta, a_idx, b_idx, one_diff
         npy_datetimestruct dts
         bint infer_dst = False, is_dst = False, fill = False
         bint shift = False, fill_nonexist = False
+        list trans_grp
+        str stamp
 
     # Vectorized version of DstTzInfo.localize
     if is_utc(tz) or tz is None:
@@ -923,7 +926,7 @@ def tz_localize_to_utc(ndarray[int64_t] vals, object tz, object ambiguous=None,
         if len(ambiguous) != len(vals):
             raise ValueError("Length of ambiguous bool-array must be "
                              "the same size as vals")
-        ambiguous_array = np.asarray(ambiguous)
+        ambiguous_array = np.asarray(ambiguous, dtype=bool)
 
     if nonexistent == 'NaT':
         fill_nonexist = True
@@ -933,7 +936,7 @@ def tz_localize_to_utc(ndarray[int64_t] vals, object tz, object ambiguous=None,
         assert nonexistent in ('raise', None), ("nonexistent must be one of"
                                                 " {'NaT', 'raise', 'shift'}")
 
-    trans, deltas, typ = get_dst_info(tz)
+    trans, deltas, _ = get_dst_info(tz)
 
     tdata = <int64_t*>cnp.PyArray_DATA(trans)
     ntrans = len(trans)
@@ -984,7 +987,7 @@ def tz_localize_to_utc(ndarray[int64_t] vals, object tz, object ambiguous=None,
         # years which is useful for checking that there is not an ambiguous
         # transition in an individual year.
         if trans_idx.size > 0:
-            one_diff = np.where(np.diff(trans_idx) != 1)[0] +1
+            one_diff = np.where(np.diff(trans_idx) != 1)[0] + 1
             trans_grp = np.array_split(trans_idx, one_diff)
 
             # Iterate through each day, if there are no hours where the
@@ -1172,13 +1175,14 @@ cdef int64_t[:] _normalize_local(int64_t[:] stamps, tzinfo tz):
     result : int64 ndarray of converted of normalized nanosecond timestamps
     """
     cdef:
-        Py_ssize_t n = len(stamps)
+        Py_ssize_t i, n = len(stamps)
         int64_t[:] result = np.empty(n, dtype=np.int64)
         ndarray[int64_t] trans
         int64_t[:] deltas
+        str typ
         Py_ssize_t[:] pos
         npy_datetimestruct dts
-        int64_t delta
+        int64_t delta, local_val
 
     if is_utc(tz):
         with nogil:
@@ -1264,6 +1268,7 @@ def is_date_array_normalized(int64_t[:] stamps, object tz=None):
         int64_t[:] deltas
         npy_datetimestruct dts
         int64_t local_val, delta
+        str typ
 
     if tz is None or is_utc(tz):
         for i in range(n):