Stratospheric data strengthens weather predictions
Scientists know that the stratosphere (the layer of atmosphere that extends from about 10 kilometres above the Earth’s surface) interacts with the troposphere, the layer of atmosphere in which we live. And that while the troposphere is chaotic and changes rapidly, the stratosphere is more stable. “The stratosphere is a vital source of information,” says SD4SP(opens in new window) project fellow Froila Palmeiro from the Euro-Mediterranean Center on Climate Change(opens in new window) (CMCC) in Italy. “The challenge is we don’t really know how interactions with the troposphere occur.” Palmeiro also notes that stratospheric data is often not included in climate service data, which is used by farmers to plan their crop activities and by renewable energy providers to anticipate sun or wind. Integrating this sort of information – with a better understanding of stratosphere-troposphere interactions – could therefore strengthen seasonal forecasting models moving forward.
Focus on the El Niño-Southern Oscillation
The SD4SP project, supported by the Marie Skłodowska-Curie Actions(opens in new window) programme, therefore set out to improve the simulation and prediction of stratospheric interactions with the troposphere. To do this, the project focused on two weather phenomena known to have a periodical impact on the North Atlantic region – the El Niño-Southern Oscillation (ENSO) and the Quasi-Biennial Oscillation (QBO). Scientists know in advance when these oscillations are likely to occur and evolve. What they don’t fully understand – and have trouble incorporating into climate models – is how the anomalies caused by these phenomena happen thousands of kilometres apart (atmospheric teleconnection). This is where a better understanding of stratosphere-troposphere interactions might help.
Strengthening seasonal forecasting models
“First, we wanted to try to disentangle how teleconnection works in ENSO and QBO,” adds Palmeiro. To do this, the project used a 3D analysis approach to examine in detail the structure of the stratospheric polar vortex. “This helped us to better understand teleconnections through stratosphere,” notes Palmeiro. “Our findings about the polar vortex for example help to explain the ‘Beast from the East’ winter storm in 2018, which brought freezing temperatures to continental Europe. We were able to see that these kinds of events are related to the splitting of the stratospheric polar vortex, which happens more frequently during La Niña (part of the ENSO cycle, and a cooler counterpart to El Niño).” The second part of the project focused on strengthening seasonal predictions. This was achieved by applying stratospheric data to weather modelling and then comparing this with what actually happened – a hindcast rather than a forecast. This enabled Palmeiro to see if her stratosphere-strengthened models were more accurate than conventional models. “We realised that there was a lot of valuable information in the stratosphere,” she remarks. “Large improvements to weather forecasting can be achieved, particularly in the North Atlantic European region.”
Disaster management and public safety
These advances in seasonal forecasting could be useful not just for the agriculture and energy sectors but also for disaster management and general public safety. More accurately predicting heavy snowfall and flooding events can ensure that appropriate action is taken in time, for example. To make this a reality, Palmeiro is currently working with international partners through global initiatives such as APARC(opens in new window), a core project of the World Climate Research Programme. “Here, I’m focusing on trying to better understand the QBO teleconnection in order to better represent the QBO in models,” she says.
