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Forecasts

Weather forecasts can be used to set the atmospheric model in RocketPy.

Here, we will showcase how to import global forecasts such as GFS, as well as local forecasts like NAM and RAP for North America, all available through OPeNDAP on the NOAA's NCEP NOMADS website. Other generic forecasts can also be imported.

Important

As a rule of thumb, forecasts can only be done for future dates. If you want to simulate your rocket launch using past data, you should use :ref:`reanalysis` or :ref:`soundings`.

Global Forecast System (GFS)

Using the latest forecast from GFS is simple. Set the atmospheric model to forecast and specify that GFS is the file you want. Note that since data is downloaded from a remote OPeNDAP server, this line of code can take longer than usual.

.. jupyter-execute::

    from datetime import datetime, timedelta
    from rocketpy import Environment

    tomorrow = datetime.now() + timedelta(days=1)

    env_gfs = Environment(date=tomorrow)

    env_gfs.set_atmospheric_model(type="forecast", file="GFS")

    env_gfs.plots.atmospheric_model()

Note

The GFS model is updated every 6 hours. It is a global model with a resolution of 0.25° x 0.25°, capable of forecasting up to 10 days into the future. For more information, visit the GFS overview page.

North American Mesoscale Forecast System (NAM)

You can also request the latest forecasts from NAM. Since this is a regional model for North America, you need to specify latitude and longitude points within North America. We will use SpacePort America for this, represented by coordinates 32.988528, -106.975056 (32°59'18.7"N 106°58'30.2"W).

.. jupyter-execute::

    env_nam = Environment(
        date=tomorrow,
        latitude=32.988528,
        longitude=-106.975056,
    )
    env_nam.set_atmospheric_model(type="forecast", file="NAM")
    env_nam.plots.atmospheric_model()

Note

The NAM model is updated every 6 hours, it has a resolution of 5 km (Regional CONUS Nest) and can forecast up to 21 points spaced by 3 hours, which means it can predict the weather for the next 63 hours (3 days). For more information, visit the NAM overview page.

Rapid Refresh (RAP)

The Rapid Refresh (RAP) model is another regional model for North America. It is similar to NAM, but with a higher resolution and a shorter forecast range. The same coordinates for SpacePort America will be used.

.. jupyter-execute::

    now = datetime.now()
    now_plus_twelve = now + timedelta(hours=12)

    env_rap = Environment(
        date=now_plus_twelve,
        latitude=32.988528,
        longitude=-106.975056,
    )
    env_rap.set_atmospheric_model(type="forecast", file="RAP")
    env_rap.plots.atmospheric_model()

Note

The RAP model, which succeeded the RUC model on May 1, 2012, offers a 13 km horizontal resolution and 50 vertical layers. RAP generates forecasts every hour for North America and Alaska.

For the CONUS region, RAP graphics are available for the latest 24 hours at hourly intervals, extending up to 51 hours for the 03, 09, 15, and 21 cycles, and up to 21 hours for other cycles.

For more details, visit: RAP Model Info.

High Resolution Window (HIRESW)

!DANGER!

HIRESW shortcut unavailable: file="HIRESW" is currently disabled in RocketPy because NOMADS OPeNDAP is deactivated for this endpoint.

If you have a HIRESW-compatible dataset from another provider (or a local copy), you can still load it explicitly by passing the path/URL in file and an appropriate mapping in dictionary.

Using Windy Atmosphere

Windy.com is a website that provides weather and atmospheric forecasts for any location worldwide. The same atmospheric predictions and data available on **windy.com** can be used in RocketPy.

The following models are accepted:

  • ECMWF-HRES
  • GFS
  • ICON-Global
  • ICON-EU (Europe only)

Let's see how to use Windy's data in RocketPy. First, we will set the location to EuRoC's launch area in Portugal.

.. jupyter-execute::

    env_windy = Environment(
        date=tomorrow,
        latitude=39.3897,
        longitude=-8.28896388889,
    )

ECMWF

We can use the ECMWF model from Windy.com.

.. jupyter-execute::

    env_windy.set_atmospheric_model(type="Windy", file="ECMWF")
    env_windy_ecmwf = env_windy
    env_windy_ecmwf.plots.atmospheric_model()

Note

The ECMWF model is a global model with a resolution of 9 km. It is updated every 12 hours and can forecast up to 10 days in advance. To learn more about the ECMWF model, visit the ECMWF website.

GFS

The GFS model is also available on Windy.com. This is the same model as described in the :ref:`global-forecast-system` section.

.. jupyter-execute::

    env_windy.set_atmospheric_model(type="Windy", file="GFS")
    env_windy_gfs = env_windy
    env_windy_gfs.plots.atmospheric_model()

ICON

The ICON model is a global weather forecasting model already available on Windy.com.

.. jupyter-execute::

    env_windy.set_atmospheric_model(type="Windy", file="ICON")
    env_windy_icon = env_windy
    env_windy_icon.plots.atmospheric_model()

Note

The ICON model is a global model with a resolution of 13 km. It is updated every 6 hours and can forecast up to 7 days in advance. For more information, visit here.

ICON-EU

The ICON-EU model is a regional weather forecasting model available on Windy.com.

env_windy.set_atmospheric_model(type="Windy", file="ICONEU")
env_windy_icon_eu = env_windy
env_windy_icon_eu.plots.atmospheric_model()

Important

The ICON-EU model is only available for Europe.

Further considerations

When using forecasts, it is important to remember that the data is not always available for the exact time you want.

Also, the servers may be down or may face high traffic.

.. seealso::

    To browse available NCEP model collections on UCAR THREDDS, visit
    `THREDDS NCEP Catalog <https://thredds.ucar.edu/thredds/catalog/grib/NCEP/GFS/Global_0p25deg/catalog.html>`_.