Articles | Volume 4, issue 1
https://doi.org/10.5194/wcd-4-249-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-4-249-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
28 Mar 2023
Research article | Highlight paper |
| 28 Mar 2023
| 28 Mar 2023
Investigation of links between dynamical scenarios and particularly high impact of Aeolus on numerical weather prediction (NWP) forecasts
Anne Martin
CORRESPONDING AUTHOR
Meteorologisches Institut München, Ludwig-Maximilians-Universität, Munich, Germany
Martin Weissmann
Institut für Meteorologie und Geophysik, Universität Wien, Vienna, Austria
Alexander Cress
Referat Datenassimilation und Vorhersagbarkeit (FE11), Deutscher Wetterdienst (DWD), Offenbach am Main, Germany
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Anne Martin, Martin Weissmann, Oliver Reitebuch, Michael Rennie, Alexander Geiß, and Alexander Cress
Atmos. Meas. Tech., 14, 2167–2183, https://doi.org/10.5194/amt-14-2167-2021, https://doi.org/10.5194/amt-14-2167-2021, 2021
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This study provides an overview of validation activities to determine the Aeolus HLOS wind errors and to understand the biases by investigating possible dependencies and testing bias correction approaches. To ensure meaningful validation statistics, collocated radiosondes and two different global NWP models, the ECMWF IFS and the ICON model (DWD), are used as reference data. To achieve an estimate for the Aeolus instrumental error the representativeness errors for the comparisons are evaluated.
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This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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This study shows that Aeolus satellite wind lidar observations significantly improve wind forecasts and that these improvements lead to more accurate rainfall predictions, particularly at longer lead times and during winter seasons in the extratropics. The benefits are likely due to better representation of large-scale atmospheric features such as jet streams and Rossby waves, highlighting Aeolus's value for numerical weather prediction.
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Initial conditions of current numerical weather prediction models insufficiently represent the sharp vertical gradients across the midlatitude tropopause. Observation-space data assimilation output is used to study the influence of assimilated radiosondes on the tropopause. The radiosondes reduce systematic biases of the model background and sharpen temperature and wind gradients in the analysis. Tropopause sharpness is still underestimated in the analysis, which may impact weather forecasts.
Maurus Borne, Peter Knippertz, Martin Weissmann, Benjamin Witschas, Cyrille Flamant, Rosimar Rios-Berrios, and Peter Veals
Atmos. Meas. Tech., 17, 561–581, https://doi.org/10.5194/amt-17-561-2024, https://doi.org/10.5194/amt-17-561-2024, 2024
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This study assesses the quality of Aeolus wind measurements over the tropical Atlantic. The results identified the accuracy and precision of the Aeolus wind measurements and the potential source of errors. For instance, the study revealed atmospheric conditions that can deteriorate the measurement quality, such as weaker laser signal in cloudy or dusty conditions, and confirmed the presence of an orbital-dependant bias. These results can help to improve the Aeolus wind measurement algorithm.
Tobias Necker, David Hinger, Philipp Johannes Griewank, Takemasa Miyoshi, and Martin Weissmann
Nonlin. Processes Geophys., 30, 13–29, https://doi.org/10.5194/npg-30-13-2023, https://doi.org/10.5194/npg-30-13-2023, 2023
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This study investigates vertical localization based on a convection-permitting 1000-member ensemble simulation. We derive an empirical optimal localization (EOL) that minimizes sampling error in 40-member sub-sample correlations assuming 1000-member correlations as truth. The results will provide guidance for localization in convective-scale ensemble data assimilation systems.
Konstantin Krüger, Andreas Schäfler, Martin Wirth, Martin Weissmann, and George C. Craig
Atmos. Chem. Phys., 22, 15559–15577, https://doi.org/10.5194/acp-22-15559-2022, https://doi.org/10.5194/acp-22-15559-2022, 2022
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A comprehensive data set of airborne lidar water vapour profiles is compared with ERA5 reanalyses for a robust characterization of the vertical structure of the mid-latitude lower-stratospheric moist bias. We confirm a moist bias of up to 55 % at 1.3 km altitude above the tropopause and uncover a decreasing bias beyond. Collocated O3 and H2O observations reveal a particularly strong bias in the mixing layer, indicating insufficiently modelled transport processes fostering the bias.
Stefan Geiss, Leonhard Scheck, Alberto de Lozar, and Martin Weissmann
Atmos. Chem. Phys., 21, 12273–12290, https://doi.org/10.5194/acp-21-12273-2021, https://doi.org/10.5194/acp-21-12273-2021, 2021
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This study demonstrates the benefits of using both visible and infrared satellite channels to evaluate clouds in numerical weather prediction models. Combining these highly resolved observations provides significantly more and complementary information than using only infrared observations. The visible observations are particularly sensitive to subgrid water clouds, which are not well constrained by other observations.
Anne Martin, Martin Weissmann, Oliver Reitebuch, Michael Rennie, Alexander Geiß, and Alexander Cress
Atmos. Meas. Tech., 14, 2167–2183, https://doi.org/10.5194/amt-14-2167-2021, https://doi.org/10.5194/amt-14-2167-2021, 2021
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This study provides an overview of validation activities to determine the Aeolus HLOS wind errors and to understand the biases by investigating possible dependencies and testing bias correction approaches. To ensure meaningful validation statistics, collocated radiosondes and two different global NWP models, the ECMWF IFS and the ICON model (DWD), are used as reference data. To achieve an estimate for the Aeolus instrumental error the representativeness errors for the comparisons are evaluated.
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Executive editor
Numerical weather prediction depends essentially on high-quality upper-air wind observations to constrain the initial conditions. This study by Martin et al. investigates the impact of spaceborne Doppler wind lidar measurements from the Aeolus mission on forecast quality of the operational global forecasting system with ICON at Deutscher Wetterdienst. An observing system experiment shows an overall beneficial impact, and the authors go one important step further and present illustrative examples how events with strong forecast quality improvements can be related to specific dynamical phenomena such as ENSO and the extratropical transition of tropical cyclones.
Numerical weather prediction depends essentially on high-quality upper-air wind observations to...
Short summary
Global wind profiles from the Aeolus satellite mission are an important recent substitute for the Global Observing System, showing an overall positive impact on numerical weather prediction forecasts. This study highlights atmospheric dynamic phenomena constituting pathways for significant improvement of Aeolus for future studies, including large-scale tropical circulation systems and the interaction of tropical cyclones undergoing an extratropical transition with the midlatitude waveguide.
Global wind profiles from the Aeolus satellite mission are an important recent substitute for...
