S2S Workshop: Summary Blog

Below is an excerpt from a blog post written by Zane Martin for the Initiative for Extreme Weather and Climate. For the full post, see the Initiative’s site.

By Zane Martin

Last week hundreds of scientists from around the world attended the Workshop on Sub-seasonal to Seasonal Predictability of Extreme Weather and Climate online and at Columbia University’s bucolic Lamont-Doherty Earth Observatory. Organized by Columbia’s International Research Institute for Climate and Society (IRI) and Initiative on Extreme Weather and Climate, in conjunction with the WWRP/WCRP Sub-seasonal to Seasonal Prediction Project and NOAA’s Modeling, Analysis, and Prediction Program (MAPP), the workshop took place over the course of two days full of diverse presentations and lively discussions.

The S2S workshop attendees on day two of the event.

The workshop addressed topics on the so-called “sub-seasonal to seasonal” (S2S) time scale, a time frame in between those of weather forecasts (less than two weeks) and seasonal climate forecasts (up to a year). The S2S window presents a significant challenge to scientists and forecasting centers because, as organizer and IRI scientist Andrew Robertson put it, the S2S time frame has historically been a “predictability desert.” As anyone planning a vacation months in advance can appreciate, weather forecasts are unreliable more than a week or two into the future. Seasonal climate forecasts, on the other hand, are largely based on ocean conditions, and predict only averages over monthly or longer periods, rather than actual weather states. The S2S time scale sits between these limits, and represents a gap in prediction skill which has, until recently, proven difficult to fill. In the last decade, though, useful predictions on this time scale have become possible, as phenomena such as the Madden-Julian oscillation (MJO), stratosphere-troposphere interactions, and others which influence weather on the time scale of 2-4 weeks have become better understood and better simulated in models.

Attendees at last week’s workshop were especially interested in “extreme” events, such as floods, droughts, heat waves, tornadoes, or hurricanes. While hugely impactful on communities and companies, these extreme events remain inherently unpredictable and difficult to forecast. A diverse range of presenters demonstrated the progress being made as well as the pressing need for continued improvement on S2S prediction. Erin Coughlan demonstrated how the Red Cross/Red Crescent makes use of S2S forecasts to anticipate and mitigate disasters, and explained how better S2S prediction would assist with budgeting and asset allocation. Michael Ventrice, from IBM’s The Weather Company, discussed the advantages S2S prediction offers to traders or clients in the energy industry looking to anticipate heat waves or cold snaps that drive demand and affect energy prices. Stefano Materia, from the Euro-Mediterranean Center on Climate Change, shared how a pair of companies in the agribusiness and water management sectors could benefit from better information predicting droughts, and discussed how to design forecasting products with policy-makers in mind.

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Read the rest of the post here.