Insight into cloud ice improves weather predictions Descriptions of secondary ice formation in mixed-phase clouds improve weather and climate modelling in the Arctic and in cold air breakout conditions. Climate Change and Environment © Thomas Richter/stock.adobe.com Clouds are an essential feature of the Earth’s energy system. They provide fresh water, and they help to regulate the climate. But mixed-phase clouds – those that contain both water and ice – are the largest source of error in climate and weather forecasting. Funded by the Marie Skłodowska-Curie Actions programme, the SIMPHAC project enhances predictive models by describing two secondary ice formation mechanisms. Cloud ice formation The primary mechanism for cloud ice formation is the development of ice crystals from aerosol particles. Secondary ice production (SIP) mechanisms are less well understood. SIMPHAC focused on descriptions of collisional break-up and drop-shattering. Collisional break-up refers to mechanical break-up upon collision of two cloud-ice particles, leading to fracturing of the smaller one. Drop-shattering refers to the shattering of water droplets as they freeze. Understanding the behaviour of mixed-phase clouds is critical to predictive forecasting. According to project coordinator Georgia Sotiropoulou: “We found that while primary ice production has been considered the most important ice formation mechanism for several decades, SIP is of similar importance and should not be ignored in atmospheric models.” Cold air breakouts SIMPHAC’s research reveals that secondary ice formation significantly impacts cold air breakout (CAO) cases, a critical weather pattern. CAOs are linked to extreme weather events, and can cause harm to crops, buildings and human life. The models developed by SIMPHAC have the potential to lead to more accurate predictions in the face of dangerous weather events. SIMPHAC has shown that collisional break-up and drop-shattering play an important role in SIP, as they are implicated in a wide range of thermodynamic conditions. Sotiropoulou says: “Including a description of collisional break-up in a weather forecasting model resulted in a more accurate prediction of the cloud fields during a CAO case.” Modelling in the Arctic SIMPHAC focused on the Arctic, the most sensitive climate region in the world. The project studied two models: the mesoscale Weather and Research Forecasting Model and the Norwegian Earth System climate model. SIMPHAC employed a methodology for explicit parametrisations developed under Vaughan Phillips to describe SIP mechanisms in the models. To evaluate the performance of the models, researchers used measurements gathered by aircraft flying north of the UK to sample CAO events. Additionally, data gathered by the Ny-Alesund research station from year-long remote sensors were used to evaluate the models as well. While the Arctic region and CAO cases in particular provide excellent opportunities to investigate SIP mechanisms, the models developed by SIMPHAC have a range of applications. Currently, the modelling tools developed by the project are being used to study ice formation in different atmospheric conditions, such as storms with extreme precipitation. Accurate forecasting is essential to managing climate change. SIMPHAC, by improving our understanding of ice formation in clouds, has helped to develop a clearer picture of how small-scale processes such as the collision of ice crystals can impact dynamic climate and weather patterns. Keywords SIMPHAC, Arctic, cold air breakout, drop-shattering, cloud ice, secondary ice production, mixed phase clouds, collisional breakup, Weather and Research Forecasting Model, Norwegian Earth System, Ny-Alesund research station
