What is ECMWF-ENS (Ensemble) weather model and how it works

The ECMWF-ENS is an ensemble weather model of one of the two major global weather forecast models in the world, on a par with the GFS, which originates from the US, yet the first one is considered the most reliable among all models. In other words, if right now you're looking at the weather forecast for the world or your city or region, it's probably from one of these two models. However, ECMWF-ENS is different from the main model with its own unique features.

In this post, you will learn about ECMWF-ENS, its working principle and the main features, and where to find the weather forecast by this model.

What is ECMWF-ENC weather forecast model?

ECMWF-ENS or sometimes EC-ENS is for Ensembles of the ECMWF (European Centre for Medium-Range Weather Forecasts), a European global forecast seamless model. It is widely regarded as the best and most reliable model currently in existence.

The model's ensembles are fabulous for weather forecasting as the range is based on many versions of the same weather forecast of the ECMWF model. According to it, "the monthly forecasting system is run 51 times from slightly different initial conditions. One forecast, called the control forecast, is run from the operational ocean and atmosphere ECMWF analyses." So they describe the vast majority of probable scenarios. Using ensembles is a powerful and modern weather forecasting approach. Do make sure to check the Ensembles, if you are looking for a more than a 3-day forecast.

Learn more about ensemble models in general and their working principles in separate article on the Windy.app blog.

The official website of the model is Ecmwf.int.

What are the main features of ECMWF-ENS weather model and how it works?

The ECMWF-ENS model has various resolutions up to tens of km. It the Windy.app it has resolution of 27 km (17 mi). The resolution is the distance between two points of the weather model grid. Bigger resolutions of 50 to 10 km in size are usually deployed in relatively flat terrains, while mountain ranges require the nodes to be a lot closer to each other, usually 5, 2, or 1 km.

The forecast depth of ECMWF-ENS weather model is 6 days. The depth of the weather forecast is the number of hours or days for which the forecast is made. As a rule, the lower the depth, the more accurate the forecast.

The ECMWF-ENS forecast step is 3 hours. The forecast step is for how long you can see a forecast in the application or on a website. There are two main step types: 1 h and 3 h.

The ECMWF-ENS updates frequency is 4 times a day (every 6 hours). The update frequency of the forecast is the regular time interval after which new forecast data is received from the supercomputers. There are models like HRRR with 24 times a day updates, but in general, the frequency of the updates of weather models is 1, 2, or rather 4 times a day.

Let's summ up the main features of ECMWF-ENS model:

Spatial resolution (grid): 27 km (17 mi)
Forecast depth (period): 6 days
Forecast step: 3 h
Forecast update frequency: 4 times a day (every 6 h)

Where to get the weather forecast from the ECMWF-ENS model?

The ECMWF-ENS weather forecast model is also the main model in the Windy.app among 10+ other models. To get a weather forecast:

1. Open your favorite or the nearest spot to your current location in the app from the Home screen or Weathe Map. To see the nearest spots, allow the app to see your location in Settings.

Home screen of the Windy.app for iOS

2. Choose ECMWF-ENS weather model in the slider under the Wind Rose:

ECMWF-ENS weather model in the Windy.app for iOS

3. Read the weather forecast from the ECMWF-ENS for your particular sport or outdoor activity. In Windy.app you can get and compare the following weather parameters using this model:

wind speed, wind direction, and wind gusts
air temperature
atmospheric pressure at the sea level

ECMWF-ENC weather parameters in the Windy.app for iOS

4. On the graph in the forecast tables you can see Max, Control, and Min values of these parameters. Let's start with the wind:

MAX (+) is the strongest wind 90% of ensemble forecasts provide
MIN (–) is the slightest
CONTROL is the middle value you can rely on

Knowing both, you could estimate the wind range in a certain time period. The more MIN and MAX derives from CONTROL, the highest the forecast uncertainty is.

Moreover, it could be useful in another way. If MIN and MAX are close, the forecast is trustworthy. In another case, you have a wide range of possible scenarios.

ECMWF-ENC weather parameters in the Windy.app for iOS

To see EC-ENS for air temperature and atmospheric pressure, choose ECMWF weather mode in the same picker and scroll down the screen:

ECMWF-ENC weather parameters in the Windy.app for iOS

5. Choose or delete one of these weather parameters using the Customization feature. That's how you will make your own custom weather profile in Windy.app.

6. Compare weather data from ECMWF-ENS model to other models in Windy.app using special Pro feature Compare mode.

ECMWF-ENC weather parameters in the Windy.app for iOS

7. You can also compare ECMWF-ENS weather forecast accuracy with other weather models thanks to special Windy.app feature based on data directly from weather stations. The weather stations are always located on the same spot's screen: