Stratosphere and Climate pages : Stratospheric Network for the Assessment of Predictability (SNAP) : UoR, Dept Of Meteorology

Stratospheric Network for the Assessment of Predictability (SNAP)

During winter and spring, the stratosphere is a dynamically exciting place, with intense and dramatic stratospheric major warming events occurring typically in two out of every three years in the Northern hemisphere and minor warming events occurring more frequently still. It is not surprising, therefore, that there has long been interest in understanding what role the stratosphere might play in influencing tropospheric weather and climate.

The SPARC SNAP project has been running since 2013 with the aim of increasing our understanding of how the stratopshere can be exploited to improve predictability on timescales between 10 and 60 days ahead. In our first phase, we were funded by a UK NERC International Opportunties Fund grant and produced work which reviewed and investigated the predictability of stratospheric variability on medium-range timescales. We performed the first major international intercomparison of straospheric predictability with partners in Japan, the USA, UK, Canada and Australia.

The next phase of our initative has shifted towards understanding and quantifying the role that the stratosphere plays in sub-seasonal predictability. The joint WWRP/WCRP Sub-seasonal to seasonal prediction project (S2S) has been and is continuing to acquire a large dataset from many operational sub-seasonal forecasting systems. The datasets contain fields in the stratosphere up to 10hPa and provide an excellent opportunity for the stratospheric community to assess the role of stratosphere in sub-seasonal predictability. Stratospheric variability is one of the main sources of predictability that can be exploited for sub-seasonal forecasting (Robertson, 2015).

The next phase of SNAP project will involve coordinated analysis of the S2S data by the SPARC community. In this site, we introduce the S2S dataset and coordinate analysis of S2S data. We also provide real-time analysis of S2S data.

We very much encourage community involvement in this project. If you would like to get involved in any capacity then please use the contact us link below to get in touch.