EGU2020-9643
https://doi.org/10.5194/egusphere-egu2020-9643
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluating Arctic meteorology modelled with the Unified Model and Integrated Forecasting System

Gillian Young1, Jutta Vüllers1, Peggy Achtert2, Paul Field1,3, Jonathan Day4, Ewan O'Connor5, Ian Brooks1, Michael Tjernström6, John Prytherch6, and Ryan Neely III1
Gillian Young et al.
  • 1School of Earth and Environment, University of Leeds, Leeds, United Kingdom (G.Young1@leeds.ac.uk)
  • 2University of Leipzig, Leipzig, Germany
  • 3Met Office, Exeter, United Kingdom
  • 4European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
  • 5Finnish Meteorological Institute, Helsinki, Finland
  • 6Stockholm University, Stockholm, Sweden

State-of-the-art numerical models such as the UK Met Office Unified Model and European Centre for Medium-Range Weather Forecasting Integrated Forecasting System are crucial tools for forecasting future Arctic warming. However, their ability to reproduce clouds and boundary layer meteorology in the high Arctic has not been thoroughly evaluated following significant model developments over the last 10 years. Model evaluation is key to understanding where remaining process weaknesses lie, thus informing further parametrization developments to improve the simulated surface energy budget.

Here, we evaluate model performance with comparison to observations made during the Arctic Ocean 2018 expedition, where a suite of remote-sensing instrumentation was active aboard the Swedish icebreaker Oden measuring summertime Arctic cloud and boundary layer properties. We find that both models do not reproduce cloud fractions well at altitude (up to 8 km) and overestimate the occurrence of low (<1 km) clouds during the sea ice melt period of the expedition. Low cloud agreement with observations improves when the sea ice begins to refreeze; however, the underestimation of cloud aloft remains consistent regardless of sea ice conditions. In this presentation, we will indicate which model processes need to be improved to capture these summertime Arctic clouds more effectively.

How to cite: Young, G., Vüllers, J., Achtert, P., Field, P., Day, J., O'Connor, E., Brooks, I., Tjernström, M., Prytherch, J., and Neely III, R.: Evaluating Arctic meteorology modelled with the Unified Model and Integrated Forecasting System, EGU General Assembly 2020, Online, 4–8 May 2020, https://doi.org/10.5194/egusphere-egu2020-9643, 2020

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