ID82: High-resolution atmospheric modeling

Details

  • Full Title

    High-resolution modeling of atmospheric processes over mountainous terrain

  • Scheduled

    Monday, 2022-09-12
    Session Part I:  13:30 - 15:00
    Session Part II: 16:00 - 17:30
    Poster Session: 17:45 - 18:30

  • Co-Conveners

    Emily Potter, Nikolina Ban

  • Assigned to Synthesis Workshop

  • Keywords

    high-resolution, modeling, regional, LES, climate, NWP

Description

High-resolution models are a valuable tool in mountain regions, both for process understand and as input for other environmental models. This is especially true when only point observations are available or when observations are sparse in general, which is often the case for mountainous regions around the world.

Numerical weather prediction and climate modeling has gone through significant improvements in the recent years, with models reaching horizontal grid spacings in the kilometric range. High horizontal resolutions lead to a more realistic representation of topography in the model domains, however, this does not necessarily improve model skill. Multiple challenges have emerged for numerical modelling over mountainous terrain: A successful simulation does not only depend on the terrain representation, but also on the quality of input data, the land-use representation, the choice of parameterizations and model setup. One of the major challenges is the correct representation of the mountain boundary layer, because turbulence parameterizations were mainly developed for horizontally homogeneous and flat terrain, considering only the vertical exchange.

This session invites submission from a broad range of numerical weather prediction and regional climate modelling approaches, such as:

  1. Model evaluation studies over mountainous terrain;
  2. Process studies;
  3. High-resolution simulations down to the large-eddy simulation range over complex terrain;
  4. Newest developments and improvements of model set-ups and parameterizations.

Registered Abstracts