Validation and assimilation of Aeolus wind observations

Martin, Anne (2023): Validation and assimilation of Aeolus wind observations. Dissertation, LMU München: Fakultät für Physik

Abstract

Along with scientific and technological developments, the advancement of the Global Observing System (GOS) has been one of the most important factors contributing to the increase in numerical weather forecasting (NWP) skill in recent years. The initial conditions of a forecast are provided by data assimilation systems, combining the latest short-range forecast with a selection of atmospheric observations. One of the current major limitations is the lack of global wind profile observations, particularly in regions and for spatial scales where geostrophic mass-wind coupling is weak. The European Space Agency's (ESA) Doppler Wind Lidar (DWL) satellite mission Aeolus provides a novel data set of wind profiles with quasi-global coverage intended to fill this gap in the GOS. This thesis aims to assess the impact of the Aeolus observations in NWP to demonstrate the potential value of such satellite-based DWL missions. A crucial prerequisite for using meteorological observations in NWP data assimilation systems is the knowledge and characterization of their errors. Therefore, in the first part of this work, a validation study is conducted to investigate the quality of the Aeolus wind profiles. Comparisons with three independent reference data sets - collocated radiosonde observations as well as model equivalents of the global ICOsahedral Nonhydrostatic (ICON) model of the German Weather Service (DWD) and the Integrated Forecast System (IFS) model of the European Centre for Medium-Range Weather Forecasts (ECMWF) - enable a comprehensive estimation of the systematic and random errors of the Aeolus observations. In addition, the systematic errors are examined for their dependencies, and correction approaches that can be used in data assimilation systems as part of quality control are tested. Discrepancies between the radiosonde and model-based validation results that occur in determining the random error are mainly due to differences in spatial and temporal representativeness. The representativeness error components can be estimated using high-resolution regional model simulations and thus can be taken into account in determining the Aeolus observational error. The results provide important information on the magnitude and vertical structure of the Aeolus Rayleigh and Mie wind error, which serves as the basis for the assigned observational error in the data assimilation. The second part of this thesis examines how numerical weather forecasting benefits from the assimilation of the novel DWL observations from the Aeolus satellite. For this purpose, an Observing System Experiment (OSE) based on the operational global assimilation system of ICON at DWD with and without the assimilation of Aeolus observations is analyzed. Besides global impact statistics, regions and periods with particularly pronounced impact are investigated further to understand the underlying dynamics leading to the overall beneficial impact. The largest impact of assimilating Aeolus observations occurs in the 2-3 day wind and temperature forecast in the tropical upper troposphere and lower stratosphere and in the Southern Hemisphere. The influence of the Aeolus observations in the Northern Hemisphere is less pronounced but still relatively large compared to other observing systems. Furthermore, this thesis illustrates three examples of atmospheric phenomena that constitute dynamical scenarios for significant forecast error reduction: the change of the oscillatory phase of two large-scale tropical circulation systems - the quasi-biennial oscillation (QBO) and the El Niño–Southern Oscillation (ENSO) - and the interaction of tropical cyclones undergoing extratropical transition (ET) with the midlatitude waveguide. These indications of dynamical changes and processes related to the particularly high impact of Aeolus on NWP forecasts provide important information for the advancement of observing and NWP systems and will serve as the basis for future studies on opportunities to improve NWP forecasts by additional observations.

• Dokumententyp: Dissertationen (Dissertation, LMU München)
• Keywords: Aeolus mission, Doppler Wind Lidar, NWP, data assimilation, observation validation, observation impact
• Themengebiete: 500 Naturwissenschaften und Mathematik ; 500 Naturwissenschaften und Mathematik > 530 Physik
• Fakultäten: Fakultät für Physik
• Sprache der Hochschulschrift: Englisch
• Datum der mündlichen Prüfung: 27. Februar 2023
• 1. Bericht­erstatter:in: Weissmann, Martin