diff --git a/city_metrix/layers/era_5_hottest_day.py b/city_metrix/layers/era_5_hottest_day.py
index eaa4ce6..44718eb 100644
--- a/city_metrix/layers/era_5_hottest_day.py
+++ b/city_metrix/layers/era_5_hottest_day.py
@@ -18,13 +18,18 @@ def __init__(self, start_date="2023-01-01", end_date="2024-01-01", **kwargs):
         self.end_date = end_date
 
     def get_data(self, bbox):
+        min_lon, min_lat, max_lon, max_lat = bbox
+        center_lon = (min_lon + max_lon) / 2
+        center_lat = (min_lat + max_lat) / 2
+
         dataset = ee.ImageCollection("ECMWF/ERA5_LAND/HOURLY")
 
         # Function to find the city mean temperature of each hour
         def hourly_mean_temperature(image):
+            point_crs = 'EPSG:4326'
             hourly_mean = image.select('temperature_2m').reduceRegion(
                 reducer=ee.Reducer.mean(),
-                geometry=ee.Geometry.BBox(*bbox),
+                geometry=ee.Geometry.Point([center_lon, center_lat], point_crs),
                 scale=11132,
                 bestEffort=True
             ).values().get(0)
@@ -49,10 +54,6 @@ def hourly_mean_temperature(image):
         day = highest_temperature_day[6:8]
         time = highest_temperature_day[-2:]
 
-        min_lon, min_lat, max_lon, max_lat = bbox
-        center_lon = (min_lon + max_lon) / 2
-        center_lat = (min_lat + max_lat) / 2
-
         # Initialize TimezoneFinder
         tf = TimezoneFinder()
         # Find the timezone of the center point
diff --git a/tests/conftest.py b/tests/conftest.py
index e140ab7..ec2563f 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -18,9 +18,21 @@ def test_create_fishnet_grid(min_x, min_y, max_x, max_y, cell_size):
     fishnet.drop('fishnet_geometry', axis=1, inplace=True)
     return fishnet
 
+
+def _create_gdf_from_coords(xmin, ymin, xmax, ymax):
+    from shapely import geometry
+    import geopandas as gp
+    geom_array = []
+    poly = geometry.Polygon(((xmin, ymin), (xmin, ymax), (xmax, ymax), (xmax, ymin)))
+    geom_array.append(poly)
+    gdf = gp.GeoDataFrame(geom_array, columns=["geometry"]).set_crs("EPSG:4326")
+    return gdf
+
+
 # Test zones of a regular 0.01x0.01 grid over a 0.1x0.1 extent by degrees
 ZONES = test_create_fishnet_grid(106.7, -6.3, 106.8, -6.2, 0.01).reset_index()
 LARGE_ZONES = test_create_fishnet_grid(106, -7, 107, -6, 0.1).reset_index()
+OR_PORTLAND_NO_TILE_ZONE = _create_gdf_from_coords(-122.7037,45.51995,-122.6923117,45.5232773)
 
 
 class MockLayer(Layer):
diff --git a/tests/test_metrics.py b/tests/test_metrics.py
index 07090af..5c6e85f 100644
--- a/tests/test_metrics.py
+++ b/tests/test_metrics.py
@@ -1,5 +1,5 @@
 from city_metrix import *
-from .conftest import ZONES, EXECUTE_IGNORED_TESTS
+from .conftest import ZONES, EXECUTE_IGNORED_TESTS, OR_PORTLAND_NO_TILE_ZONE
 import pytest
 
 
@@ -24,6 +24,12 @@ def test_built_land_without_tree_cover():
     assert expected_zone_size == actual_indicator_size
 
 
+@pytest.mark.skipif(EXECUTE_IGNORED_TESTS == False, reason="CDS API needs personal access token file to run")
+def test_era_5_met_preprocess_portland():
+    indicator = era_5_met_preprocessing(OR_PORTLAND_NO_TILE_ZONE)
+    assert len(indicator) == 24
+
+
 @pytest.mark.skipif(EXECUTE_IGNORED_TESTS == False, reason="CDS API needs personal access token file to run")
 def test_era_5_met_preprocess():
     indicator = era_5_met_preprocessing(ZONES)