Sensitivities of the Madden–Julian oscillation forecasts to configurations of physics in the ECMWF global model
<p>The sensitivities of the Madden–Julian oscillation (MJO) forecasts to various different configurations of the parameterized physics are examined with the global model of ECMWF's Integrated Forecasting System (IFS). The motivation for the study was to simulate the MJO as a nonlinear fr...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2021-03-01
|
Series: | Atmospheric Chemistry and Physics |
Online Access: | https://acp.copernicus.org/articles/21/4759/2021/acp-21-4759-2021.pdf |
Summary: | <p>The sensitivities of the Madden–Julian oscillation (MJO) forecasts to various different configurations of the
parameterized physics are examined with the global model of ECMWF's Integrated
Forecasting System (IFS). The motivation for the study was to simulate
the MJO as a nonlinear free wave under active interactions with
higher-latitude Rossby waves. To emulate free dynamics in the IFS, various
momentum-dissipation terms (“friction”) as well as diabatic heating were
selectively turned off over the tropics for the range of the latitudes from
20<span class="inline-formula"><sup>∘</sup></span> S to 20<span class="inline-formula"><sup>∘</sup></span> N. The reduction of friction sometimes improves the MJO forecasts,
although without any systematic tendency. Contrary to the original motivation,
emulating free dynamics with an operational forecast model turned out to be
rather difficult, because forecast performance sensitively depends on the
specific type of friction turned off. The result suggests the need for
theoretical investigations that much more closely follow the actual
formulations of model physics: a naive approach with a dichotomy of with or
without friction simply fails to elucidate the rich behaviour of complex
operational models. The paper further exposes the importance of physical
processes other than convection for simulating the MJO in global forecast
models.</p> |
---|---|
ISSN: | 1680-7316 1680-7324 |