diff --git a/pepsico/app_calc.py b/pepsico/app_calc.py
index f7ecb461..4f65b3ce 100644
--- a/pepsico/app_calc.py
+++ b/pepsico/app_calc.py
@@ -113,7 +113,7 @@ def seasonal_data(monthly_data, start_month, end_month, start_year=None, end_yea
 
 def seasonal_wwc(
     labelled_season_data, variable, frost_threshold, wet_threshold, hot_threshold,
-    warm_nights_spell, dry_spell,
+    warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
 ):
     # Boolean variables need the additional where to return NaNs from False/0 to Nans
     # and the sum parameters for entirely NaNs seasons to remain NaNs and not turn to
@@ -253,6 +253,16 @@ def seasonal_wwc(
             .map(median_length_of_spells, "T", min_spell_length=dry_spell)
         )
         wwc_units = "days"
+    if variable == "rain_events":
+        data_ds = (
+            labelled_season_data
+            .groupby(labelled_season_data["seasons_starts"])
+            .map(
+                number_extreme_events_within_days, threshold=rain_event_amount,
+                window=rain_event_window,
+            )
+        )
+        wwc_units = ""
     # This is all a bit tedious but I didn't figure out another way to keep
     # seasons_ends and renaming time dim T
     # Can revisit later if this code has a future
@@ -763,17 +773,21 @@ def number_extreme_events_within_days(
     Examples
     --------
     Number of rain events of >80mm in 2 days or less:
-    number_extreme_events_within_days(rain_daily_data_in_mm, "gt", 80, 2)    
+    number_extreme_events_within_days(rain_daily_data_in_mm, 80, 2)    
     """
-    count = 0
-    dd = daily_data.copy()
-    #Start with shortest events
-    for w in range(1, window+1):
-        for t in range(len(dd[dim])-(w-1)):
-            #Assert new event
-            new_event = dd.isel({dim: slice(t, t+w)}).sum(dim) > threshold
-            #Mask days having formed a new event so that they won't account again
-            #for following events (t loop) or longer events (w loop)
-            dd[{dim: slice(t, t+w)}] = dd[{dim: slice(t, t+w)}].where(~new_event)
-            count = count + new_event
+
+    # Initiatlize accumulated rain, event window and even count
+    acc = daily_data.isel({dim: 0}, drop=True)
+    w = xr.ones_like(acc, dtype=int)
+    count = ((acc > threshold) * 1).where(~np.isnan(acc))
+    for i in range(1, daily_data[dim].size):
+        data_i = daily_data.isel({dim: i}, drop=True)
+        # Increment if accumulated not met yet to form an event 
+        # AND max size of window not met yet
+        increment_condition = (acc <= threshold).where(~np.isnan(acc)) and (w < window)
+        # If not incrementing, restart accumulating rain and event window length
+        acc = (acc + data_i).where(increment_condition, other=data_i)
+        w = (w + 1).where(increment_condition, other=1)
+        # Update event count of accumulated rain exceeded threshold
+        count = count + (acc > threshold).where(~np.isnan(acc))
     return count
diff --git a/pepsico/pixi.lock b/pepsico/pixi.lock
index c71c77dd..e16a13ac 100644
--- a/pepsico/pixi.lock
+++ b/pepsico/pixi.lock
@@ -1,6 +1,301 @@
 version: 6
 environments:
   default:
+    channels:
+    - url: https://conda.anaconda.org/conda-forge/
+    options:
+      pypi-prerelease-mode: if-necessary-or-explicit
+    packages:
+      linux-64:
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/affine-2.4.0-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.15.3-hb03c661_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aom-3.9.1-hac33072_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/attrs-26.1.0-pyhcf101f3_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-auth-0.10.1-h2d2dd48_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.9.13-h2c9d079_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.12.6-hb03c661_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-compression-0.3.2-h8b1a151_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-http-0.10.12-h4bacb7b_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.26.3-hc87160b_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-s3-0.11.5-h6d69fc9_5.conda
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+  size: 13387
+  timestamp: 1760831448842
 - conda: https://conda.anaconda.org/conda-forge/linux-64/intel-gmmlib-22.10.0-hb700be7_0.conda
   sha256: bc231d69eb6663db0e09738fb916c5e5507147cf1ac60f364f964004e0b29bab
   md5: 10909406c1b0e4b57f9f4f0eb0999af8
@@ -2955,6 +3277,16 @@ packages:
   license_family: MIT
   size: 5251872
   timestamp: 1772628857717
+- conda: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.6.0-pyhf9edf01_1.conda
+  sha256: e14aafa63efa0528ca99ba568eaf506eb55a0371d12e6250aaaa61718d2eb62e
+  md5: d7585b6550ad04c8c5e21097ada2888e
+  depends:
+  - python >=3.9
+  - python
+  license: MIT
+  license_family: MIT
+  size: 25877
+  timestamp: 1764896838868
 - conda: https://conda.anaconda.org/conda-forge/linux-64/proj-9.7.1-he0df7b0_3.conda
   sha256: c94d3d8ef40d1ea018860d66c416003bc03adede7d212efc9218bb64041fe2f7
   md5: 031e33ae075b336c0ce92b14efa886c5
@@ -3058,6 +3390,15 @@ packages:
   license_family: Apache
   size: 1155153
   timestamp: 1775918132188
+- conda: https://conda.anaconda.org/conda-forge/noarch/pygments-2.20.0-pyhd8ed1ab_0.conda
+  sha256: cf70b2f5ad9ae472b71235e5c8a736c9316df3705746de419b59d442e8348e86
+  md5: 16c18772b340887160c79a6acc022db0
+  depends:
+  - python >=3.10
+  license: BSD-2-Clause
+  license_family: BSD
+  size: 893031
+  timestamp: 1774796815820
 - conda: https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.3.2-pyhcf101f3_0.conda
   sha256: 417fba4783e528ee732afa82999300859b065dc59927344b4859c64aae7182de
   md5: 3687cc0b82a8b4c17e1f0eb7e47163d5
@@ -3078,6 +3419,25 @@ packages:
   license_family: BSD
   size: 21085
   timestamp: 1733217331982
+- conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.0.3-pyhc364b38_1.conda
+  sha256: 960f59442173eee0731906a9077bd5ccf60f4b4226f05a22d1728ab9a21a879c
+  md5: 6a991452eadf2771952f39d43615bb3e
+  depends:
+  - colorama >=0.4
+  - pygments >=2.7.2
+  - python >=3.10
+  - iniconfig >=1.0.1
+  - packaging >=22
+  - pluggy >=1.5,<2
+  - tomli >=1
+  - exceptiongroup >=1
+  - python
+  constrains:
+  - pytest-faulthandler >=2
+  license: MIT
+  license_family: MIT
+  size: 299984
+  timestamp: 1775644472530
 - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.4-habeac84_100_cp314.conda
   build_number: 100
   sha256: dec247c5badc811baa34d6085df9d0465535883cf745e22e8d79092ad54a3a7b
@@ -3505,6 +3865,16 @@ packages:
   license_family: BSD
   size: 3301196
   timestamp: 1769460227866
+- conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
+  sha256: 91cafdb64268e43e0e10d30bd1bef5af392e69f00edd34dfaf909f69ab2da6bd
+  md5: b5325cf06a000c5b14970462ff5e4d58
+  depends:
+  - python >=3.10
+  - python
+  license: MIT
+  license_family: MIT
+  size: 21561
+  timestamp: 1774492402955
 - conda: https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.15.0-h396c80c_0.conda
   sha256: 7c2df5721c742c2a47b2c8f960e718c930031663ac1174da67c1ed5999f7938c
   md5: edd329d7d3a4ab45dcf905899a7a6115
diff --git a/pepsico/pixi.toml b/pepsico/pixi.toml
index 44fe17e5..d22812d1 100644
--- a/pepsico/pixi.toml
+++ b/pepsico/pixi.toml
@@ -19,3 +19,10 @@ dash-bootstrap-components = ">=2.0.4,<3"
 scipy = ">=1.17.1,<2"
 zarr = ">=3.1.6,<4"
 sqlalchemy = ">=2.0.49,<3"
+
+[feature.dev.dependencies]
+pytest = "*"
+
+[environments]
+default = {features = ["dev"], solve-group = "prod"}
+prod = {features = [], solve-group = "prod"}
diff --git a/pepsico/proj_wwc/layout.py b/pepsico/proj_wwc/layout.py
index 96ace797..69bc75db 100644
--- a/pepsico/proj_wwc/layout.py
+++ b/pepsico/proj_wwc/layout.py
@@ -38,7 +38,7 @@ def app_layout():
                     id="variable",
                     options=[
                         "warm_nights",
-                        # "rain_events",
+                        "rain_events",
                         "mean_Tmax",
                         "mean_Tmin",
                         "dry_days",
@@ -57,7 +57,7 @@ def app_layout():
                     ],
                     labels=[
                         "Warm Nights",
-                        # "Count of Rain Events",
+                        "Count of Rain Events",
                         "Mean Max Temperature",
                         "Mean Min Temperature",
                         "Count of Dry Days",
@@ -77,6 +77,26 @@ def app_layout():
                     init=1,
                 )),
                 Block("Definitions",
+                    "Rain event: ",
+                    Number(
+                        id="ret",
+                        default=80,
+                        min=0,
+                        max=999,
+                        width="5em",
+                        debounce=False,
+                    ),
+                    "mm or more; ",
+                    "within: ",
+                    Number(
+                        id="rew",
+                        default=2,
+                        min=1,
+                        max=99,
+                        width="5em",
+                        debounce=False,
+                    ),
+                    "days or less ",
                     "Frost <=",
                     Number(
                         id="frost",
@@ -274,6 +294,13 @@ def app_layout():
                     temperature is lesser or equal than a user-defined threshold.
                 """
             ]),
+            html.P([
+                html.B("Count of Rain Events (rain_events):"),"""
+                    Number of rain events in the season. A rain event accumulates 
+                    a user-defined threshold in mm or more in a user-defined number 
+                    of days or less.
+                """
+            ]),
         ),
         
         lou.map(GLOBAL_CONFIG["zoom"]),
diff --git a/pepsico/proj_wwc/maproom.py b/pepsico/proj_wwc/maproom.py
index 59e3d5d5..dd5c9893 100644
--- a/pepsico/proj_wwc/maproom.py
+++ b/pepsico/proj_wwc/maproom.py
@@ -103,7 +103,7 @@ def select_var(variable):
         ]:
             data_var = "tasmax"
         if variable in [
-            # "rain_events",
+            "rain_events",
             "dry_days",
             "wet_days",
             "longest_dry_spell",
@@ -122,6 +122,7 @@ def local_data(
         model, variable,
         start_day, start_month, end_day, end_month,
         frost_threshold, wet_threshold, hot_threshold, warm_nights_spell, dry_spell,
+        rain_event_amount, rain_event_window,
     ):
         model = [model] if model != "Multi-Model-Average" else [
             "GFDL-ESM4", "IPSL-CM6A-LR", "MPI-ESM1-2-HR","MRI-ESM2-0", "UKESM1-0-LL"
@@ -163,7 +164,7 @@ def local_data(
                     data_ds, start_day, start_month, end_day, end_month,
                 ),
                 variable, frost_threshold, wet_threshold, hot_threshold,
-                warm_nights_spell, dry_spell,
+                warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
             )
         return data_ds, error_msg
 
@@ -232,12 +233,15 @@ def invalid_button(lat, lng, lat_min, lng_min, lat_max, lng_max):
         State("hot", "value"),
         State("wms", "value"),
         State("dryspell", "value"),
+        State("ret", "value"),
+        State("rew", "value"),
         prevent_initial_call=True,
     )
     def send_data_as_csv(
         n_clicks, marker_pos, region, variable,
         start_day, start_month, end_day, end_month,
         frost_threshold, wet_threshold, hot_threshold, warm_nights_spell, dry_spell,
+        rain_event_amount, rain_event_window,
     ):
         lat = marker_pos[0]
         lng = marker_pos[1]
@@ -250,12 +254,14 @@ def send_data_as_csv(
         hot_threshold = float(hot_threshold)
         warm_nights_spell = int(warm_nights_spell)
         dry_spell = int(dry_spell)
+        rain_event_amount = float(rain_event_amount)
+        rain_event_window = int(rain_event_window)
         model = "Multi-Model-Average"
         data_ds, error_msg = local_data(
             lat, lng, model, variable,
             start_day, start_month, end_day, end_month,
             frost_threshold, wet_threshold, hot_threshold,
-            warm_nights_spell, dry_spell,
+            warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
         )
         if error_msg == None :
             lng_units = "E" if (lng >= 0) else "W"
@@ -292,12 +298,15 @@ def send_data_as_csv(
         State("hot", "value"),
         State("wms", "value"),
         State("dryspell", "value"),
+        State("ret", "value"),
+        State("rew", "value"),
     )
     def local_plots(
         marker_pos, region, n_clicks, model, variable,
         start_day, end_day, start_month, end_month,
         start_year, end_year, start_year_ref, end_year_ref,
         frost_threshold, wet_threshold, hot_threshold, warm_nights_spell, dry_spell,
+        rain_event_amount, rain_event_window,
     ):
         lat = marker_pos[0]
         lng = marker_pos[1]
@@ -325,11 +334,13 @@ def local_plots(
             hot_threshold = float(hot_threshold)
             warm_nights_spell = int(warm_nights_spell)
             dry_spell = int(dry_spell)
+            rain_event_amount = float(rain_event_amount)
+            rain_event_window = int(rain_event_window)
             data_ds, error_msg = local_data(
                 lat, lng, model, variable,
                 start_day, start_month, end_day, end_month,
                 frost_threshold, wet_threshold, hot_threshold,
-                warm_nights_spell, dry_spell,
+                warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
             )
             if error_msg != None :
                 local_graph = pingrid.error_fig(error_msg)
@@ -491,6 +502,7 @@ def seasonal_change(
         start_day, end_day, start_month, end_month,
         start_year, end_year, start_year_ref, end_year_ref,
         frost_threshold, wet_threshold, hot_threshold, warm_nights_spell, dry_spell,
+        rain_event_amount, rain_event_window,
     ):
         model = [model] if model != "Multi-Model-Average" else [
             "GFDL-ESM4", "IPSL-CM6A-LR", "MPI-ESM1-2-HR","MRI-ESM2-0", "UKESM1-0-LL"
@@ -507,7 +519,7 @@ def seasonal_change(
                     start_day, start_month, end_day, end_month,
                 ),
                 variable, frost_threshold, wet_threshold, hot_threshold,
-                warm_nights_spell, dry_spell,
+                warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
             ).mean(dim="T", keep_attrs=True) for m in model
         ], "M").mean("M", keep_attrs=True)
         data = xr.concat([
@@ -521,7 +533,7 @@ def seasonal_change(
                     start_day, start_month, end_day, end_month,
                 ),
                 variable, frost_threshold, wet_threshold, hot_threshold,
-                warm_nights_spell, dry_spell,
+                warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
             ).mean(dim="T", keep_attrs=True) for m in model
         ], "M").mean("M", keep_attrs=True)
         #Tedious way to make a subtraction only to keep attributes (units)
@@ -570,12 +582,15 @@ def map_attributes(data, variable):
         State("hot", "value"),
         State("wms", "value"),
         State("dryspell", "value"),
+        State("ret", "value"),
+        State("rew", "value"),
     )
     def draw_colorbar(
         region, n_clicks, scenario, model, variable,
         start_day, end_day, start_month, end_month,
         start_year, end_year, start_year_ref, end_year_ref,
         frost_threshold, wet_threshold, hot_threshold, warm_nights_spell, dry_spell,
+        rain_event_amount, rain_event_window,
     ):
         start_day = int(start_day)
         end_day = int(end_day)
@@ -585,13 +600,15 @@ def draw_colorbar(
         wet_threshold = float(wet_threshold)
         hot_threshold = float(hot_threshold)
         warm_nights_spell = int(warm_nights_spell)
+        rain_event_amount = float(rain_event_amount)
+        rain_event_window = int(rain_event_window)
         dry_spell = int(dry_spell)
         data = seasonal_change(
             scenario, model, variable, region,
             start_day, end_day, start_month, end_month,
             start_year, end_year, start_year_ref, end_year_ref,
             frost_threshold, wet_threshold, hot_threshold,
-            warm_nights_spell, dry_spell,
+            warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
         )
         colorbar, min, max = map_attributes(data, variable)
         return (
@@ -621,12 +638,15 @@ def draw_colorbar(
         State("hot", "value"),
         State("wms", "value"),
         State("dryspell", "value"),
+        State("ret", "value"),
+        State("rew", "value"),
     )
     def make_map(
         region, n_clicks, scenario, model, variable,
         start_day, end_day, start_month, end_month,
         start_year, end_year, start_year_ref, end_year_ref,
         frost_threshold, wet_threshold, hot_threshold, warm_nights_spell, dry_spell,
+        rain_event_amount, rain_event_window,
     ):
         try:
             send_alarm = False
@@ -635,7 +655,8 @@ def make_map(
                 f"{variable}/{start_day}/{end_day}/{start_month}/{end_month}/"
                 f"{start_year}/{end_year}/{start_year_ref}/{end_year_ref}/"
                 f"{frost_threshold}/{wet_threshold}/{hot_threshold}/"
-                f"{warm_nights_spell}/{dry_spell}"
+                f"{warm_nights_spell}/{dry_spell}/{rain_event_amount}/"
+                f"{rain_event_window}"
             )
         except:
             url_str= ""
@@ -653,7 +674,7 @@ def make_map(
             f"<variable>/<start_day>/<end_day>/<start_month>/<end_month>/"
             f"<start_year>/<end_year>/<start_year_ref>/<end_year_ref>/"
             f"<frost_threshold>/<wet_threshold>/<hot_threshold>/<warm_nights_spell>/"
-            f"<dry_spell>"
+            f"<dry_spell>/<rain_event_amount>/<rain_event_window>"
         ),
         endpoint=f"{config['core_path']}"
     )
@@ -662,6 +683,7 @@ def fcst_tiles(tz, tx, ty,
         start_day, end_day, start_month, end_month,
         start_year, end_year, start_year_ref, end_year_ref,
         frost_threshold, wet_threshold, hot_threshold, warm_nights_spell, dry_spell,
+        rain_event_amount, rain_event_window,
     ):
         start_day = int(start_day)
         end_day = int(end_day)
@@ -672,12 +694,14 @@ def fcst_tiles(tz, tx, ty,
         hot_threshold = float(hot_threshold)
         warm_nights_spell = int(warm_nights_spell)
         dry_spell = int(dry_spell)
+        rain_event_amount = float(rain_event_amount)
+        rain_event_window = int(rain_event_window)
         data = seasonal_change(
             scenario, model, variable, region,
             start_day, end_day, start_month, end_month,
             start_year, end_year, start_year_ref, end_year_ref,
             frost_threshold, wet_threshold, hot_threshold,
-            warm_nights_spell, dry_spell,
+            warm_nights_spell, dry_spell, rain_event_amount, rain_event_window,
         )
         (
             data[select_var(variable)].attrs["colormap"],
diff --git a/pepsico/test/test_app_calc.py b/pepsico/test/test_app_calc.py
index d8169698..27a2da47 100644
--- a/pepsico/test/test_app_calc.py
+++ b/pepsico/test/test_app_calc.py
@@ -2,6 +2,7 @@
 import pandas as pd
 import xarray as xr
 import app_calc
+import time
 
 
 def test__cumsum_flagged_diff():
@@ -139,7 +140,9 @@ def test_number_extreme_events_within_days():
     t = pd.date_range(start="2000-05-01", end="2000-05-10", freq="1D")
     values = 1 + 0*np.arange(t.size)
     precip = xr.DataArray(values, coords={"T": t})
+    start = time.time()
     count = app_calc.number_extreme_events_within_days(precip, 2, 3)
+    print(time.time() - start)
 
     np.testing.assert_array_equal(count, [3])
-    
+    assert False