Why is it so difficult to represent stably stratified conditions in NWP models?

Title
Why is it so difficult to represent stably stratified conditions in NWP models?
Technical memorandum
Date Published
08/2012
Secondary Title
ECMWF Technical Memoranda
Number
684
Author
Irina Sandu
Anton Beljaars
Peter Bechtold
T. Mauritsen
Gianpaolo Balsamo
Publisher
ECMWF
Abstract In the 1990's scientists at ECMWF suggested that artificially enhancing turbulent diffusion in stable conditions improves the representation of two important aspects of weather forecasts, i.e. near-surface temperatures and synoptic cyclones. Since then, this practice has often been used for tuning the large-scale performance of operational Numerical Weather Prediction (NWP) models, although it is widely recognised to be detrimental for an accurate representation of stable boundary layers. Here we investigate why, 20 years on, such a compromise is still needed in the ECMWF model. We find that reduced turbulent diffusion in stable conditions improves the representation of winds in stable boundary layers, but it deteriorates the large-scale flow and the near-surface temperatures. This suggests that enhanced diffusion is still needed to compensate for errors caused by other poorly represented processes. Among these, we identify the orographic drag, which influences the large-scale flow in a similar way to the turbulence closure for stable conditions, and the strength of the land-atmosphere coupling, which partially controls the near-surface temperatures. We also take a closer look at the relationship between the turbulence closure in stable conditions and the large-scale flow, which was not investigated in detail with a global NWP model. We demonstrate that the turbulent diffusion in stable conditions affects the large-scale flow by modulating the strength of synoptic cyclones and anticyclones, but also the amplitude of the planetary-scale standing waves.
URL https://www.ecmwf.int/en/elibrary/76284-why-it-so-difficult-represent-stably-stratified-conditions-nwp-models
DOI 10.21957/0lt9ztj22
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