diff --git a/bpeng/weather/weather.py b/bpeng/weather/weather.py
index d2f0f7486062d4976b045837cca945b0636e08a1..238a1e0c8f49fda2ea6271ffed5c9b6113a50699 100644
--- a/bpeng/weather/weather.py
+++ b/bpeng/weather/weather.py
@@ -1,6 +1,8 @@
 """ Weather scraper for wunderground.com """
-from datetime import date, timedelta
+from flask import current_app
+from datetime import date, datetime, timedelta
 from urllib.request import urlopen
+import dateutil.parser
 
 import json
 import numpy as np
@@ -45,6 +47,7 @@ class WeatherUnderground:
     # WUNDER_URL = 'https://www.wunderground.com/history/airport/{}/{}/DailyHistory.html?format=1'
     # url above is deprecated
     WUNDER_JSON = 'http://api.wunderground.com/api/{}/history_{}/q/{}/{}.json'
+    WUNDER_JSON_FUTURE = 'http://api.wunderground.com/api/{}/hourly10day/q/{}/{}.json'
     MIN_ALLOWED_TEMPERATURE = -100  # The minimum allowed value for temperature
     temperature = None
     humidity = None
@@ -105,18 +108,54 @@ class WeatherUnderground:
         Raises:
             KeyError: API Key does not exist or exceeds limit.
         """
-        url = self.WUNDER_JSON.format(self.api_key, day.replace('/', ''),
-                                      self.state, self.city)
-        data = json.loads(urlopen(url).read().decode())
-        try:
-            data = data['history']['observations']
-        except Exception as _:
-            raise KeyError('Key does not exist or exceeds limit.')
-        features = pd.DataFrame(data)[['date', 'tempi', 'hum', 'precipi', 'wspdi']].dropna()
-        features['hour'] = features['date'].apply(lambda x: x['hour'])
+
+        current_app.logger.info('Getting weather for {}'.format(day))
+        date = dateutil.parser.parse(day)
+
+        # Handle future date entirely with hourly forecast
+        if date.date() > datetime.today().date():
+            return self.get_future_date_weather(day)
+        else:
+            url = self.WUNDER_JSON.format(self.api_key, day.replace('/', ''),
+                                          self.state, self.city)
+            data = json.loads(urlopen(url).read().decode())
+            try:
+                data = data['history']['observations']
+            except Exception as _:
+                raise KeyError('Key does not exist or exceeds limit.')
+            features = pd.DataFrame(data)[['date', 'tempi', 'hum', 'precipi', 'wspdi']].dropna()
+            features['hour'] = features['date'].apply(lambda x: x['hour'])
+            features = features[features['tempi'].astype(float) >= self.MIN_ALLOWED_TEMPERATURE]
+            # If it's the same day, we also have to add future data
+            if date.date() == datetime.today().date():
+                new_features = self.get_future_date_weather(day)
+                features = features.append(new_features)
+            return features
+
+    def get_future_date_weather(self, day):
+        url = self.WUNDER_JSON_FUTURE.format(self.api_key, self.state, self.city)
+        response = json.loads(urlopen(url).read().decode())
+        data = []
+        for row in response['hourly_forecast']:
+            row_date = '{}/{}/{}'.format(
+                row['FCTTIME']['year'],
+                row['FCTTIME']['mon_padded'],
+                row['FCTTIME']['mday_padded'],
+            )
+            if row_date == day:
+                data.append(row)
+        if not len(data):
+            raise ValueError('No hourly data for the specified future data. Future data only available 10 days ahead')
+        features = pd.DataFrame(data)[['FCTTIME', 'temp', 'humidity', 'qpf', 'wspd']].dropna()
+        features['hour'] = features['FCTTIME'].apply(lambda x: x['hour_padded'])
+        features['tempi'] = features['temp'].apply(lambda x: x['english'])
+        features['wspdi'] = features['wspd'].apply(lambda x: x['english'])
+        features['precipi'] = features['qpf'].apply(lambda x: x['english'])
+        features['hum'] = features['humidity']
         features = features[features['tempi'].astype(float) >= self.MIN_ALLOWED_TEMPERATURE]
         return features
 
+
     @staticmethod
     def add_missing_temperature(hour_temperature_list):
         """
@@ -173,17 +212,13 @@ class WeatherUnderground:
         """
         self.api_key = api_key
         for day in self.day_list:
-            try:
-                # All of the weather data for that day
-                day_weather = self.get_date_weather(day)
-                hour_temp = day_weather[['tempi', 'hour']]
-                self.temperature.append(self.add_missing_temperature(hour_temp))
-                self.humidity.append(self.average_of_feature(day_weather['hum']))
-                self.wind.append(self.average_of_feature(day_weather['wspdi']))
-                self.rain.append(self.sum_of_rain(day_weather['precipi']))
-
-            except Exception as err:
-                raise ValueError('No temperature data for {}, {}'.format(day, str(err)))
+            # All of the weather data for that day
+            day_weather = self.get_date_weather(day)
+            hour_temp = day_weather[['tempi', 'hour']]
+            self.temperature.append(self.add_missing_temperature(hour_temp))
+            self.humidity.append(self.average_of_feature(day_weather['hum']))
+            self.wind.append(self.average_of_feature(day_weather['wspdi']))
+            self.rain.append(self.sum_of_rain(day_weather['precipi']))
 
         # Detailed dataframe with hourly temperature data
         dataframe_list = []