CFAN, Climate Forecast Applications Network, LLC.

                                                       © 2019.  All Rights Reserved 

  • Twitter Social Icon
  • LinkedIn Social Icon

 Telephone:  USA  +1.404.803.2012

 Email:  info@cfanclimate.com 

Seasonal Forecasts

CFAN's seasonal forecasting solution combines state-of-the-art model-based forecast systems with a statistical/dynamical approach and predictability analysis that into a seasonal forecast product that consistently has better skill than our competitors.  

Using seasonal climate forecast information in your decision making process requires an assessment of the confidence you can place in our forecast. Seasonal predictability can vary depending on the time of the year, location, and climatic regime. CFAN's comprehensive predictability and uncertainty analysis provides unique and critical information for your decision making process.

CFAN’s seasonal forecast product is based on both ECMWF and NOAA’s CFS model:

  • Monthly forecast summary provided by the 10th of the month

  • Provides overview of temperature and precipitation anomalies for next 6 months for the US and Europe

  • US temperature exceedance graphics capture probabilistic view of temperature anomaly risk across the US

  • Additional in-depth meteorological components include: hemispheric height and temperature anomalies, ENSO, sea surface temperatures and teleconnections

  • In-depth summary report made available via the website contains key components from website along with additional analysis via ensemble clustering

 

CFAN also provides statistical forecasts of seasonal temperatures for the U.S., using an innovative data mining approach that is driven by our climate dynamics analysis.  An overview of our approach is described by our presentation to the Weather Risk Management Association [link]

 

We are currently developing a hybrid seasonal forecast scheme that synthesizes the advantages of the global climate models with the predictors identified using our climate dynamics approach.