First Results From The TEAMx-FLOW Project: Wintertime Radiosonde Observations And Numerical Modelling Of Mountain Waves Over The Tyrolean Alps

The TEAMx programme is a coordinated international research programme focusing on improving our understanding of exchange processes in the atmosphere over mountains and evaluating their representation in numerical weather prediction (NWP) and climate models. TEAMx features several observational and modelling strategies conducted by nationally funded projects centred on the European Alps, including 6-week extended observational periods (EOPs) in both summer and winter 2025. In this presentation, we present the first results from the UK-funded TEAMx-FLOW project, which focuses on the representation of wintertime orographic drag from mountain waves across spatial scales (including sub-km) in the UK Met Office Unified Model (UM) and its evaluation against TEAMx observations. Here we present analysis of the first of these observations, an intensive radiosonde balloon campaign launched throughout January-March 2025 conducted by the UK National Centre for Atmospheric Science (NCAS). The NCAS campaign featured 6-hourly operational launches, complemented with 3-hourly intensive launch periods during mountain wave events and also simultaneous launches of offset pairs of radiosondes. We analyse and quantify mountain waves and their momentum transport in these measurements, including using cross-spectral analysis of the offset pairs to obtain scale separation of observed mountain waves, a process not routinely applied to balloon soundings before. We also explore observations of partial wave breakdown in horizontally sheared flow, a process highly challenging to represent in models. With these new observations, we outline how the representation of mountain waves across multiple spatial scales in the UM and other NWP models can be evaluated and improved to achieve ever more accurate sub-km modelling, leading to improved predictions of mountain weather and climate in next-generation models.