Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016
Numerical weather forecast systems like the ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) are known to be affected by a moist bias in the extratropical lowermost stratosphere (LMS) which results in a systematic cold bias there. We use high-spatial-res...
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ftdoajarticles:oai:doaj.org/article:e6127417fdd44764a6b2dc5fea318bbf 2023-05-15T16:30:23+02:00 Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016 W. Woiwode A. Dörnbrack I. Polichtchouk S. Johansson B. Harvey M. Höpfner J. Ungermann F. Friedl-Vallon 2020-12-01T00:00:00Z https://doi.org/10.5194/acp-20-15379-2020 https://doaj.org/article/e6127417fdd44764a6b2dc5fea318bbf EN eng Copernicus Publications https://acp.copernicus.org/articles/20/15379/2020/acp-20-15379-2020.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-20-15379-2020 1680-7316 1680-7324 https://doaj.org/article/e6127417fdd44764a6b2dc5fea318bbf Atmospheric Chemistry and Physics, Vol 20, Pp 15379-15387 (2020) Physics QC1-999 Chemistry QD1-999 article 2020 ftdoajarticles https://doi.org/10.5194/acp-20-15379-2020 2022-12-31T07:44:36Z Numerical weather forecast systems like the ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) are known to be affected by a moist bias in the extratropical lowermost stratosphere (LMS) which results in a systematic cold bias there. We use high-spatial-resolution water vapor measurements by the airborne infrared limb-imager GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) during the PGS (POLSTRACC/GW-LCYCLE-II/SALSA) campaign to study the LMS moist bias in ECMWF analyses and 12 h forecasts from January to March 2016. Thereby, we exploit the two-dimensional observational capabilities of GLORIA, when compared to in situ observations, and the higher vertical and horizontal resolution, when compared to satellite observations. Using GLORIA observations taken during five flights in the polar sub-vortex region around Scandinavia and Greenland, we diagnose a systematic moist bias in the LMS exceeding + 50 % (January) to + 30 % (March) at potential vorticity levels from 10 PVU ( ∼ highest level accessed with suitable coverage) to 7 PVU. In the diagnosed time period, the moist bias decreases at the highest and driest air masses observed but clearly persists at lower levels until mid-March. Sensitivity experiments with more frequent temporal output, and lower or higher horizontal and vertical resolution, show the short-term forecasts to be practically insensitive to these parameters on timescales of < 12 h. Our results confirm that the diagnosed moist bias is already present in the initial conditions (i.e., the analysis) and thus support the hypothesis that the cold bias develops as a result of forecast initialization. The moist bias in the analysis might be explained by a model bias together with the lack of water vapor observations suitable for assimilation above the tropopause. Article in Journal/Newspaper Greenland Directory of Open Access Journals: DOAJ Articles Greenland Atmospheric Chemistry and Physics 20 23 15379 15387 |
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English |
topic |
Physics QC1-999 Chemistry QD1-999 |
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Physics QC1-999 Chemistry QD1-999 W. Woiwode A. Dörnbrack I. Polichtchouk S. Johansson B. Harvey M. Höpfner J. Ungermann F. Friedl-Vallon Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016 |
topic_facet |
Physics QC1-999 Chemistry QD1-999 |
description |
Numerical weather forecast systems like the ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) are known to be affected by a moist bias in the extratropical lowermost stratosphere (LMS) which results in a systematic cold bias there. We use high-spatial-resolution water vapor measurements by the airborne infrared limb-imager GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) during the PGS (POLSTRACC/GW-LCYCLE-II/SALSA) campaign to study the LMS moist bias in ECMWF analyses and 12 h forecasts from January to March 2016. Thereby, we exploit the two-dimensional observational capabilities of GLORIA, when compared to in situ observations, and the higher vertical and horizontal resolution, when compared to satellite observations. Using GLORIA observations taken during five flights in the polar sub-vortex region around Scandinavia and Greenland, we diagnose a systematic moist bias in the LMS exceeding + 50 % (January) to + 30 % (March) at potential vorticity levels from 10 PVU ( ∼ highest level accessed with suitable coverage) to 7 PVU. In the diagnosed time period, the moist bias decreases at the highest and driest air masses observed but clearly persists at lower levels until mid-March. Sensitivity experiments with more frequent temporal output, and lower or higher horizontal and vertical resolution, show the short-term forecasts to be practically insensitive to these parameters on timescales of < 12 h. Our results confirm that the diagnosed moist bias is already present in the initial conditions (i.e., the analysis) and thus support the hypothesis that the cold bias develops as a result of forecast initialization. The moist bias in the analysis might be explained by a model bias together with the lack of water vapor observations suitable for assimilation above the tropopause. |
format |
Article in Journal/Newspaper |
author |
W. Woiwode A. Dörnbrack I. Polichtchouk S. Johansson B. Harvey M. Höpfner J. Ungermann F. Friedl-Vallon |
author_facet |
W. Woiwode A. Dörnbrack I. Polichtchouk S. Johansson B. Harvey M. Höpfner J. Ungermann F. Friedl-Vallon |
author_sort |
W. Woiwode |
title |
Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016 |
title_short |
Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016 |
title_full |
Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016 |
title_fullStr |
Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016 |
title_full_unstemmed |
Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016 |
title_sort |
technical note: lowermost-stratosphere moist bias in ecmwf ifs model diagnosed from airborne gloria observations during winter–spring 2016 |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/acp-20-15379-2020 https://doaj.org/article/e6127417fdd44764a6b2dc5fea318bbf |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland |
genre_facet |
Greenland |
op_source |
Atmospheric Chemistry and Physics, Vol 20, Pp 15379-15387 (2020) |
op_relation |
https://acp.copernicus.org/articles/20/15379/2020/acp-20-15379-2020.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-20-15379-2020 1680-7316 1680-7324 https://doaj.org/article/e6127417fdd44764a6b2dc5fea318bbf |
op_doi |
https://doi.org/10.5194/acp-20-15379-2020 |
container_title |
Atmospheric Chemistry and Physics |
container_volume |
20 |
container_issue |
23 |
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15379 |
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15387 |
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