diff --git a/tests/geospatial/test_climatology.py b/tests/geospatial/test_climatology.py
index 9148e9cda5..1318943768 100644
--- a/tests/geospatial/test_climatology.py
+++ b/tests/geospatial/test_climatology.py
@@ -39,7 +39,8 @@ def compute_rolling_mean(ds: xr.Dataset, window_weights: xr.DataArray) -> xr.Dat
     stacked = stacked.fillna(stacked.sel(dayofyear=365))
     stacked = stacked.pad(pad_width={"dayofyear": half_window_size}, mode="wrap")
     stacked = stacked.rolling(dayofyear=window_size, center=True).construct("window")
-    return stacked.weighted(window_weights).mean(dim=("window", "year"))
+    rolling = stacked.weighted(window_weights).mean(dim=("window", "year"))
+    return rolling.isel(dayofyear=slice(half_window_size, -half_window_size))
 
 
 def create_window_weights(window_size: int) -> xr.DataArray:
@@ -78,7 +79,7 @@ def test_compute_climatology(client, gcs_url, scale):
     # Load dataset
     ds = xr.open_zarr(
         "gs://weatherbench2/datasets/era5/1959-2023_01_10-wb13-6h-1440x721_with_derived_variables.zarr",
-    )  # .drop_encoding()
+    )
 
     if scale == "small":
         # 101.83 GiB (small)
@@ -96,22 +97,24 @@ def test_compute_climatology(client, gcs_url, scale):
     ds = ds[variables].sel(time=time_range)
 
     ds = ds.drop_vars([k for k, v in ds.items() if "time" not in v.dims])
-    input_chunks_without_time = {
-        dim: chunks for dim, chunks in ds.chunks.items() if dim != "time"
-    }
-    pencil_chunks = {"time": -1, "longitude": 4, "latitude": 4}
-    ds = ds.chunk(pencil_chunks)
+    pencil_chunks = {"time": -1, "longitude": "auto", "latitude": "auto"}
 
+    working = ds.chunk(pencil_chunks)
     hours = xr.DataArray(range(0, 24, 6), dims=["hour"])
-    daysofyear = xr.DataArray(range(0, 367), dims=["dayofyear"])
+    daysofyear = xr.DataArray(range(1, 367), dims=["dayofyear"])
     template = (
-        ds.isel(time=0)
+        working.isel(time=0)
         .drop_vars("time")
         .expand_dims(hour=hours, dayofyear=daysofyear)
         .assign_coords(hour=hours, dayofyear=daysofyear)
     )
-    ds = ds.map_blocks(compute_hourly_climatology, template=template)
+    working = working.map_blocks(compute_hourly_climatology, template=template)
 
-    pancake_chunks = {"hour": 1, "dayofyear": 1, **input_chunks_without_time}
-    ds = ds.chunk(pancake_chunks)
-    ds.to_zarr(gcs_url, storage_options={"token": CoiledShippedCredentials()})
+    pancake_chunks = {
+        "hour": 1,
+        "dayofyear": 1,
+        "latitude": ds.chunks["latitude"],
+        "longitude": ds.chunks["longitude"],
+    }
+    result = working.chunk(pancake_chunks)
+    result.to_zarr(gcs_url, storage_options={"token": CoiledShippedCredentials()})