Lexington, Mass., August 21, 2007 — Verification of sCast™, AER's seasonal forecast was published this week in the Journal of Climate, a peer-reviewed publication of the American Meteorological Society.
The research for this highly regarded statistical approach to long range winter forecasting, funded by the National Science Foundation, was found to "work well in accurately predicting winter conditions over much of the eastern United States and Northern Eurasia", according to Jay Fein, NSF's Atmospheric Sciences Program Director. NSF issued a press release highlighting sCast's unique linkage between snow cover in Siberia and winter temperatures in the U.S. (See www.nsf.gov/news "Scientists Verify Predictive Model for Winter Weather").
sCast™ has been used operationally since 1999 by major investment firms and more recently by hedge funds, energy and weather derivatives traders. For more information, please contact Marketing@aer.com
About AER, Inc.
Atmospheric and Environmental Research, Inc. (www.aer.com), established in 1977 and headquartered in Lexington, Massachusetts, is an award winning environmental research and consulting company with demonstrated expertise in remote sensing, radiative transfer, ensemble weather prediction, oceanography, space weather, atmospheric modeling, planetary sciences, and a provider of medium and long range forecasts for the Energy and Financial Markets.
About the Science:
Unlike other seasonal forecasts, sCast uses a unique initialization scheme as input to its climate model. Our input is a combination of El Niño temperature trends in addition to snow cover from remote parts of the world and the North Atlantic Oscillation and Arctic Oscillation patterns. This provides a more complete indication of the overall forcing and allows more accurate seasonal forecasting than other models that incorporate only ocean-based factors in predicting seasonal climate, including El Niño.
For a copy of the verification report, please contact your eCast Account Manager or see the forecast verification article “Improved Skill of Northern Hemisphere Winter Surface Temperature Predictions Based on Land–Atmosphere Fall Anomalies”, in the American Meteorological Society’s Journal of Climate.