Browsing by Subject "WRF"
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Publication Climate dynamics : the performance of seasonal ensemble forecast for improving food security in Ethiopia(2023) Ware, Markos Budusa; Wulfmeyer, VolkerPart one of this thesis aims to define homogenous climatic regions using objective clustering methods and characterize seasonal cycles, trends, and anomalies in precipitation and temperature. Climate-based on amplifies inherent spatiotemporal climate variability in the Horn of Africa due to global, regional, coastal, and local processes. The homogeneous climatic regions and synoptic circulation types were defined using Principal Component Analysis (PCA) PCA–K-means and PCA–Ward’s. Using the decision criteria of respective algorithms, four homogenous climatic regions were determined for Ethiopia. These climatic regions were distinctive in their seasonal cycles, trends, and anomalies in annual and seasonal precipitation and temperature. These results highlight that the trends in precipitation and temperature vary not only between climatic regions but also by rainy seasons. The short rains (received between November and December) increased by 50 mm/decade in the southwestern region where the evergreen forest meets with the long rainy season. The mean annual and seasonal temperature increased between 0.3 and 0.6 °C/decade virtually in all climatic regions. Regionalization methods were sensitive to spatial domain size but not to the length of the time series. Climatology of sea-level air pressure showed decreasing northward trend over the study domain, as did the temperature, wind velocity, and relative humidity at 500 hPa. However, geopotential height at 500 hPa and temperature at 850 hPa decreased toward the south over the domain. Circulation types were defined by applying PCA on a composite matrix of the six variables. From the first five Principal Components (PCs), ten circulation types (CTs) were defined over East Africa and then associated with environmental events. CTs clearly distinguished rainy seasons comprising different atmospheric states responsible for varying weathers. The summer season was described by a combination of strong positive anomalies in temperature at 850 hPa, northeasterly winds, and Somali jet at 500 hPa, and weak negative anomalies in temperature at 500 hPa. Trends in the number of days categorized in different CTs showed a significant variation among the groups. The drought events, defined using the consecutive dry days (CDD), correspond with positive anomalies in temperature at 850 hPa, northwesterly and Somali Jet, and negative anomalies in relative humidity at 500 hPa. Flooding, defined using a proxy of 80 mm/day per grid cell, was associated with strong westerly winds at 500 hPa, strong positive anomalies in temperature at the lower troposphere, strong easterlies and southwesterly, and positive anomalies in relative humidity at 500 hPa. Part two of the thesis aims to assess the performance of the seasonal ensemble forecast over the Horn of Africa for improving food security. A seasonal forecast with a horizon of up to seven months offers a great opportunity for agricultural optimization, which results in an improved economy and food security. For this purpose, the Weather Research and Forecasting (WRF) model was applied for dynamical downscaling of the latest seasonal forecasting system version 5 (SEAS5) for summer 2018 with different microphysics parameterizations, and initial and boundary conditions. Downscaling was performed by a horizontal resolution of 3 km over the topographically complex domain of East Africa. The seasonal ensemble forecast was evaluated using probabilistic metrics like the Brier skill score, probability ranking score, continuous probability ranking score, discrimination score, and ignorance score. The results of the WRF showed that the model has a strong warm bias in the 2m temperature and a wet bias in precipitation. The relative operating characteristics (ROC) curve showed a higher predicting probability of 2m temperature in below-normal and above-normal terciles over northern Ethiopia and the Indian Ocean, where the model performed better, highlighting the advantage of high-resolution simulations compared to ERA5. The median and distribution of WRF, SEAS5, and ERA5 showed remarkable variation between the homogenous climatic regions. Especially the summer of 2018 was wetter relative to climatology, and WRF overestimated this condition in the region.Publication Model evaluation and data assimilation impact studies in the framework of COPS(2012) Schwitalla, Thomas; Wulfmeyer, VolkerThe 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.Publication Studies of soil-vegetation-atmosphere feedback processes with WRF on the convection permitting scale(2017) Milovac, Josipa; Wulfmeyer, VolkerLand system models which can incorporate land-atmosphere and human-environment interactions are vital for reliable climate projections in heterogeneous agricultural landscapes. At resolutions fine enough to resolve detailed land use, models need a sophisticated representation of planetary boundary layer (PBL) and land surface processes in order to predict changes in key quantities like precipitation or temperatures. Assessment of turbulence schemes and land surface models (LSM) is fundamental therefore not only to advance model development, but also to understand important phenomena like feedbacks within the soil-vegetation-atmosphere (SVA) continuum. Up until now however, a lack of appropriate observations has impeded any comprehensive assessments. Here, through comparisons with so far unique profile measurements, the study investigates the impact of using different PBL schemes and LSMs, and explores how SVA feedbacks are simulated by the model. Using the Weather Research and Forecasting (WRF) model, a six member ensemble was run, at a convection permitting resolution, with varying combinations of LSMs (NOAH and NOAH-MP) and PBL schemes (two local and two non-local approaches). The analysis was performed for two case studies – a dry and a convective weather situation – in three different locations in Germany. During the dry case, key convective PBL (CBL) features were analysed, and the simulations were compared with high resolution water vapour differential absorption lidar measurements. For the convective case, the focus was on exploring the model representation of the pre-convective environment and the ensuing convection and precipitation. In both cases, the nature of the simulated SVA feedback processes was assessed through an innovative “mixing diagram” approach. Results show that the nonlocal PBL schemes produce a drier and higher CBL than the local schemes. These results are sensitive to parameters calculated in the surface layer schemes, which are themselves often paired with PBL schemes. Furthermore, the NOAH‑MP LSM produces drier atmospheric conditions than NOAH, with a difference in mixing ratio profiles ranging up to 1.4 gkg-1. These variations are more pronounced in the upper CBL than close to the ground. The mixing diagrams indicate that these deviations are mainly related to entrainment fluxes. In the dry case, NOAH-MP’s dry air entrainment is up to 6 times higher than with NOAH, while in the convective case the difference is not as pronounced (up to 1.5 higher with NOAH-MP). This suggests that the difference in the simulation of the CBL between the two LSMs is strongly linked to the surface energy partitioning – the higher the Bowen ratio, the greater the difference between the LSMs. Thus, WRF appears to be more sensitive to the choice of LSM at higher Bowen ratios. NOAH and NOAH-MP exhibit marked differences in representing atmospheric variables such as moisture. Those differences are not constrained to the lower atmosphere close to the land surface, but extended to the lower troposphere. The variations in free tropospheric moisture between the LSMs strongly affects the nature of the simulated convection, and associated precipitation. The degree of sensitivity of the spatial variability and amount of the precipitation with respect to the selection of LSM and PBL scheme shows a strong dependence on the analysed region. A distinct finding of this thesis is the greater sensitivity of WRF with respect to the PBL development to the selection of the LSM, than to the PBL scheme. Furthermore, the impact of this sensitivity is not constrained to the lower CBL, but extends up to the interfacial layer and the lower troposphere - for both dry and convective weather conditions. On the other hand, it is clear that the simulated coupling strength between the land surface and atmosphere is very sensitive to the surface Bowen ratio. The synergies between high resolution measurements and model simulations, with an advanced representation of the land surface processes, will facilitate not only further development of parameterization schemes, but also an improvement in our understanding of land-atmosphere interactions.