Seasonal Wind Speed Anomaly Forecasts

Vortex SEASONAL. Forecasts for wind speed anomalies over periods up to 12 months using Copernicus Climate Change Service (C3S) seasonal forecast datasets. We provide you not only with the model outputs for the next month but also with a Vortex seasonal prediction adjusted to your site.

When to use SEASONAL?

  • When you need to plan revenues or production some quarters in advance.
  • When you need accurate monthly predictions.
  • When planning wind farm operations, maintenance and construction for the months ahead.

Technical details:

  • Wind speed anomaly forecasts up to 6 months ahead on a monthly basis.
  • Wind speed anomaly forecasts up to 12 months ahead on a quarterly, six-monthly or yearly basis.
  • 30-year hourly time series at 3 km horizontal resolution as climate reference.
  • Map layers.
  • Ensemble-mean fields up to 6 months ahead.
  • Global seasonal forecast maps from different seasonal models (ECMWF, NCEP, UK MetOffice, Meteo France, DWD, CMCC, JMA).
  • Wind speed anomaly maps up to 6 months ahead on a monthly, quarterly or six-monthly basis.
  • Maps are available to download in kmz format.
  • Site-specific monthly wind speed anomaly forecasts up to 12 months ahead with the Vortex SEASONAL model.
  • Predictability information for each forecast is calculated from past model performance.
  • Monthly site-specific climatology analysis for wind speed and anomalies.
  • Interactive Seasonal interface with all data to analyse.
  • Monthly site-specific report.

More information

Vortex SEASONAL uses Copernicus Climate Change Service (C3S) seasonal forecast datasets, which are provided by European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met OfficeMétéo-France, the German Weather Service (Deutscher Wetterdienst, DWD), the Euro-Mediterranean Center on Climate Change (Centro Euro-Mediterraneo sui Cambiamenti Climatici, CMCC), the US National Weather ServiceNCEP (National Centers for Environmental Prediction, NCEP), and the Japan Meteorological Agency (JMA).

These models are initialized with data describing the systems state at the starting point of the forecast, and then they are used to predict the evolution of this state over time. While ensembles can describe the uncertainties coming from inaccurate knowledge of the initial conditions of the components of the Earths system, uncertainty arising from approximations made in the models is very much dependent on the choice of model used. A convenient way to quantify the effect of these approximations is to combine outputs from several independently developed, initialized, and operated models.

The wind speed anomaly maps recap all ensembles of each meteorological center. The ensemble mean is used as average information to summarise all of them.

New monthly forecasts are launched on the 1st day of the month and released on the 13th day by C3S. Every 14th day of the month, we update maps for the current and next two months.

Monthly wind speed anomaly forecasts are calculated as a percentage from monthly-mean forecasts over monthly-mean hindcasts (retrospective forecast). The retrospective forecasts are initialized at equivalent intervals over the period 1993-2016. The ensemble-mean anomalies are then computed concerning the corresponding model climate for each model.

Download the technical details and validation document and find here more detailed information about Vortex SEASONAL methodology: “Using the Copernicus datasets, statistics and artificial intelligence to beat climatology“.

Interested in Vortex SEASONAL?