Browsing by Person "Schwitalla, Thomas"

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Model evaluation and data assimilation impact studies in the framework of COPS
(2012) Schwitalla, Thomas; Wulfmeyer, Volker
The goal of this thesis was the study of new approaches for improving and investigating quantitative precipitation forecasting (QPF), e.g., by optimizing model resolution, physics combination, and data assimilation. A forecasting system based on the Mesoscale Model 5 (MM5) was compared against other operational numerical weather prediction models from Meteo France, MeteoSwiss and the German Weather Service primarily with respect to daytime precipitation. First, a notable daytime dry bias was observed. It appears to be the result of a too small high-resolution domain and the switched-off convection parameterization from the second to the innermost domain. Even the application of a 4-dimensional variational data assimilation (4DVAR) with GPS slant total delays (STD) does not solve this problem due to inconsistent model physics between the 4DVAR and the forecasting model. Nevertheless, the MM5 is in good agreement with the shape of the observed diurnal cycle after the spin-up phase. As the development of the MM5 was suspended, a transition to the new Weather Research and Forecasting (WRF) model system was made after the D-PHASE period (end of 2007). This system features state-of-the-art physics packages and also a variational data assimilation system. As a new observing system, GPS Zenith Total Delay (ZTD) data from Central Europe were incorporated into the 3-dimensional variational data assimilation (3DVAR) system to further improve the initial water vapor field. A first study with this system revealed an improvement of the integrated water vapor RMSE of about 15% and a small but positive impact on the spatial and quantitative precipitation forecast. Additionally, the importance of assimilating upper air observations and the necessity to select a large, convection permitting model domain emerged. Finally a rapid update cycle (RUC) approach, comparable to operational forecast centers, has been developed for a convection-permitting configuration of the WRF model. The system is capable to assimilate radar observations from Germany and France, GPS-ZTD data and satellite radiances and can be applied even for near real-time applications. First experiments with this system show promising results in comparison to other operational models.
A multivariate approach to drought monitoring: Improving robustness and accuracy through a new drought index in regions with high climate variability, applied to the drought-prone region of Ethiopia
(2026) Kebede, Abebe; Warrach-Sagi, Kirsten; Schwitalla, Thomas; Wulfmeyer, Volker; Abebe, Tesfaye; Tadesse, Tsegaye
Study focus: Assessing, monitoring, and quantifying drought characteristics to develop early warning systems is crucial for identifying the spatial extent and severity of droughts at regional and local scales especially in regions of vulnerable societies relying on local agriculture. Observations and reanalysis from 1981 to 2022 are analyzed for spatiotemporal droughts in Ethiopia. While standard drought indices like Standardized Precipitation Index and Standardized Soil Moisture Index are based solely on precipitation or soil moisture, a new drought index based on precipitation, potential evaporation, surface temperature, soil temperature, and soil moisture is developed, making the index more robust to climate and land use changes. This new Multivariate Standardized Drought Index (MvrSDI) is evaluated focusing on the severity and duration of 2015 and 2022 droughts in Ethiopia. Results show that spatiotemporal comparisons of MvrSDI at 3-, 6-, and 12-month time scales detect drought severity and duration in each drought-prone region of Ethiopia. Further,Mann-Kendall statistic test identifiy a drought trend between 1981 and 2022 an increasing drought severity. New hydrological insight for the region: The MvrSDI effectively assesses and monitors drought impacts on agriculture, proving beneficial for stakeholders focused on environmental sustainability and food security. Its multivariate character makes MvrSDI more robust and therefore a valuable tool for drought monitoring and decision-making in regions with high climate variability and land use changes in drought-prone regions like Ethiopia.
Soil moisture–atmosphere coupling strength over central Europe in the recent warming climate
(2025) Schwitalla, Thomas; Jach, Lisa; Wulfmeyer, Volker; Warrach-Sagi, Kirsten
In recent decades Europe has experienced severe droughts and heatwaves. Notably, precipitation in central Europe exhibited strong dry anomalies during the summers of 2003, 2018, and 2022. This phenomenon has significant implications for agriculture, ecosystems, and human societies, highlighting the need to understand the underlying mechanisms driving these events. Despite significant advancements in understanding land–atmosphere (LA) coupling, the temporal variability in LA coupling strength and its associated impacts remain poorly understood. This study aims to quantify the variability in LA coupling strength over central Europe during the summer seasons from 1991 to 2022, with a focus on the relationships between temperature, soil moisture, precipitation, and large-scale weather patterns. Our results reveal that interannual variability occurs in different coupling relationships throughout the summer seasons, with significant implications for climate extremes, agriculture, and ecosystems. The increasing frequency of warm and dry summers from 2015 onwards hints at extended periods of reduced soil moisture available for evapotranspiration and the likelihood of locally triggered convection. This study provides new insights into the dynamics of LA coupling, highlighting the importance of considering the interannual variability in LA coupling strength in climate modeling and prediction, particularly in the context of a warming climate.