Scientists verify accuracy of Siberian snow cover climate model

Scientists at the US National Science Foundation have verified the accuracy of a model that uses October snow cover in Siberia to predict upcoming winter temperatures and snowfall in the high - and mid - latitudes of the Northern Hemisphere.

Washington, Aug 21 : Scientists at the US National Science Foundation have verified the accuracy of a model that uses October snow cover in Siberia to predict upcoming winter temperatures and snowfall in the high - and mid - latitudes of the Northern Hemisphere.

The model is called 'sCast', short for seasonal forecast model, said atmospheric scientist Judah Cohen of AER, Inc., in Lexington, Massachusetts.

Together with colleagues, Cohen analysed seven real-time winter forecasts and 33 winter hindcasts (simulations of winters going back to 1972) to verify 'sCast'.

"sCast works well in accurately predicting winter conditions over much of the eastern United States and Northern Eurasia. Dynamical model prediction of winter climate remains a formidable challenge, and statistical approaches such as Cohen's continue to be a valuable alternative," said Jay Fein, program director in the National Science Foundation (NSF)'s Division of Atmospheric Sciences, which funded the research.

Fein said October is the month when snow begins to pile up across Siberia. It is also the month that the Siberian high, one of three dominant weather centres across the Northern Hemisphere, forms.

In years when Siberian snow cover is above normal, a strengthened Siberian high and colder surface temperatures across Northern Eurasia develop in the fall, said Cohen.

"The result is a warming in Earth's stratosphere that occurs in January. This eventually descends from the stratosphere to Earth's surface over a week or two in January, making for a warmer winter in Northern Hemisphere high latitudes," said Cohen.

"However, in mid-latitudes it turns colder, so winters in the northeastern US and Eastern Europe are likely to be colder and snowier than normal. The skill of the sCast model takes us the next step beyond current seasonal forecast models employed worldwide," he said.

The results appear in this week's issue of the Journal of Climate.

ANI