Parameterisation of sea ice cover in short-range regional numerical weather prediction

• Main Author: Batrak, Yurii
• Other Authors: Tietsche, Steffen, University of Helsinki, Faculty of Science, Doctoral Programme in Atmospheric Sciences, Development Centre for Weather Forecasting, Norwegian Meteorological Institute, Helsingin yliopisto, matemaattis-luonnontieteellinen tiedekunta, Ilmakehätieteiden tohtoriohjelma, Helsingfors universitet, matematisk-naturvetenskapliga fakulteten, Doktorandprogrammet i atmosfärvetenskap
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Helsingin yliopisto 2022
• Subjects: meteorology; Arctic; Arctic Ocean; Climate change; Sea ice
• Online Access: http://hdl.handle.net/10138/346384

With the ongoing climate change economic activity in the Arctic steadily increases and it is expected to grow further in the coming years. However, harsh weather conditions of the present-day Arctic place strong demands for accurate and timely weather forecasts, which nowadays are obtained by means of numerical weather prediction. Sea ice covers a considerable part of the Arctic Ocean and numerical weather prediction systems operating in the region require a reliable and computationally-efficient representation of the sea ice cover in the model. Traditionally, simplified one-dimensional parameterisation schemes are applied for this task. However, implications of utilising such schemes in the context of contemporary high-resolution regional operational numerical weather prediction are not well studied. The present work aims to assess these effects through a series of numerical experiments in the operational-like environment. A new one-dimensional parameterisation scheme, allowing for varying level of complexity, implemented in the HARMONIE-AROME numerical weather prediction system, is used as the main research tool. The findings show that applying an over-simplified parameterisation scheme can result in considerable deterioration of the ice surface temperature field in the model. Errors in the modelled ice surface temperature influence the turbulent exchange between the ice surface and the model atmosphere, and, as a result, the near-surface atmospheric variables, such as the screen-level air temperature. Thus, improving the ice surface temperature in the model results in a positive impact on the atmospheric forecast of these parameters. Therefore, a sea ice scheme within an operational numerical weather prediction system should preferably include an explicit representation of the snow layer to accurately represent the surface energy budget of sea ice. Applying a sea ice data assimilation procedure to assimilate a near real time satellite ice surface temperature product in HARMONIE-AROME further reduces the root ...