Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016
<p>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-sp...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2020-12-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/20/15379/2020/acp-20-15379-2020.pdf |
| _version_ | 1818721429678456832 |
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| 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 |
| collection | DOAJ |
| description | <p>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 <span class="inline-formula">+</span>50 % (January) to <span class="inline-formula">+</span>30 % (March) at potential vorticity levels from 10 PVU (<span class="inline-formula">∼</span> 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 <span class="inline-formula"><</span> 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.</p> |
| first_indexed | 2024-12-17T20:38:36Z |
| format | Article |
| id | doaj.art-e6127417fdd44764a6b2dc5fea318bbf |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-17T20:38:36Z |
| publishDate | 2020-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-e6127417fdd44764a6b2dc5fea318bbf2022-12-21T21:33:23ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242020-12-0120153791538710.5194/acp-20-15379-2020Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016W. Woiwode0A. Dörnbrack1I. Polichtchouk2S. Johansson3B. Harvey4M. Höpfner5J. Ungermann6F. Friedl-Vallon7Institute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Karlsruhe, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyEuropean Centre for Medium-Range Weather Forecasts, Reading, UKInstitute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Karlsruhe, GermanyNational Centre for Atmospheric Science, University of Reading, Reading, UKInstitute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Karlsruhe, GermanyInstitute of Energy and Climate Research – Stratosphere (IEK-7), Forschungszentrum Jülich, Jülich, GermanyInstitute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany<p>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 <span class="inline-formula">+</span>50 % (January) to <span class="inline-formula">+</span>30 % (March) at potential vorticity levels from 10 PVU (<span class="inline-formula">∼</span> 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 <span class="inline-formula"><</span> 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.</p>https://acp.copernicus.org/articles/20/15379/2020/acp-20-15379-2020.pdf |
| spellingShingle | 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 Atmospheric Chemistry and Physics |
| title | 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_short | 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 |
| url | https://acp.copernicus.org/articles/20/15379/2020/acp-20-15379-2020.pdf |
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