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 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.
In addition to private companies, other attendees affiliated with operational forecast and government centers, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), the World Meteorological Organization, and the Australian Bureau of Meteorology, all brought unique perspectives. Also in attendance were research scientists from labs like NOAA’s Geophysical Fluid Dynamics Laboratory or NASA’s Jet Propulsion Laboratory, in addition to professors and academics from universities around the world. The presentations addressed pragmatic considerations such as how to best construct and evaluate forecast systems; specific problems in atmospheric dynamics, such as how the stratosphere influences “atmospheric rivers”, giant plumes of water vapor which can cause floods on the US West Coast; or broader climate science questions, such as where is the boundary between predictable “signal” and unpredictable “noise”.
The workshop organizers encouraged early-career scientists and graduate students such as myself to attend, and underscored the possibilities of and the necessity for the next generation of scientists to continue work on S2S issues. I was inspired and excited by the community’s enthusiasm and by the scientific challenges facing S2S prediction. S2S research is an emerging area where there are ample opportunities to contribute to advancing scientific understanding, as well as the possibility to have meaningful impacts on the business, government, and nonprofit sectors. The S2S time scale is a frontier in our efforts to gain understanding and improve prediction of weather and climate, and progress will naturally require collaboration among individuals from diverse communities and viewpoints.
The S2S project, now officially in its third year, has already advanced research significantly through the S2S database – an ongoing collection of forecasts and re-forecasts on S2S time scales up to around 60 days which are provided by modeling centers around the globe. The S2S database offers a relatively new and unprecedented resource for scientists, modeling groups, and interested parties to better study, understand, and ultimately improve S2S prediction – in the same way that the Coupled Model Intercomparison Project (CMIP) archives have advanced climate change research – by making output from many models available publicly in a single place. Several presenters, including one of the database’s main organizers, ECMWF senior scientist Frederic Vitart, demonstrated new or preliminary results from the S2S database, but it is only beginning to be exploited. Many participants supported by the NOAA MAPP program for research projects using the database (including two projects at Columbia, one led by Suzana Camargo on tropical cyclones and one led by Shuguang Wang on the MJO) are still in the early phases of their work.
At the conclusion of the conference, attendees were asked to look to the future – towards what the S2S project should become and where the community should focus its efforts. Participants left thinking about how to engage other organizations interested in S2S prediction, how to further improve the S2S database, and how to implement academic advances at operational forecast centers. While it was clear there were still significant scientific, computing, and operational challenges to be confronted, the tone was one of enthusiasm and optimism as the workshop came to a close.