Euripides Avgoustoglou

The limited availability of wind profile measurements has long hindered advancements in atmospheric modeling and our understanding of climate systems. The European Space Agency’s (ESA) “Aeolus” mission encountered this challenge with the groundbreaking introduction of space-based Doppler wind lidar technology, capable of providing Near-Real-Time wind profile data. The regional COSMO NWP model was utilized to demonstrate the potential of “Aeolus” in improving NWP model capabilities. The research focuses on analyzing the precipitation of the severe Hephaestion storm, which struck Greece in early January 2020, by comparing the performance of the NWP model with and without the assimilation of “Aeolus” data.

Storm Daniel is arguably one of the most severe Mediterranean tropical-like cyclones (medicanes) ever recorded. Greece was one of the most affected areas, especially the central part of the country. The extreme precipitation that was observed along with the subsequent extensive flooding was considered a critical challenge to validate the regional version of the ICON (Icosahedral Non-Hydrostatic) numerical weather prediction (NWP) model. From a methodological standpoint, the short-range nature of the model was realized with 48 h runs over a sequence of cases that covered the storm period. The development of the medicane was highlighted via the tracking of the minimum mean sea level pressure (MSLP) in reference to the corresponding analysis of the European Center for Medium-Range Weather Forecasts (ECMWF). In a similar fashion, snapshots regarding the 500 hPa geopotential associated with the 850 hPa temperature were addressed at the 24th forecast hour of the model runs. Although the model’s performance over the four most affected synoptic stations of the Hellenic National Meteorological Service (HNMS) was mixed, the overall accumulated forecasted precipitation was in very good agreement with the corresponding total value of the observations over all the available synoptic stations.

The study of atmospheric models and climate systems has been hampered by the restricted availability of wind profile measurements. By recording wind profiles in near real time and giving useful information for Numerical Weather Prediction (NWP) models, the Doppler wind lidar technology used in the European Space Agency’s Aeolus mission is expected to unravel this problem. By analyzing the precipitation from IANOS medicane, which occurred over the Thessaly plain in September 2020, a case study utilizing the COSMO NWP model illustrates the potential usefulness of Aeolus data in strengthening NWP models. Run in hindcast mode and forced by analyses with and without Aeolus, the model assimilated data that were produced at the European Centre for Medium-Range Forecasts (ECMWF). Evaluation against observations from Greek synoptic stations showed that the model precipitation using the Aeolus-assimilated data preponderated over the model results without their inclusion. This work aims to demonstrate the additional value of the Aeolus project towards the expansion of our knowledge of Earth’s atmosphere, particularly the improvement of our capacity to estimate severe weather events via the use of Aeolus with NWP models.

The ICON (icosahedral non-hydrostatic) numerical weather prediction model (NWP)’s sensitivity is evaluated for the geographical area of Greece. As ICON model has recently been endorsed operationally by the Members of the COSMO (Consortium for Small-scale Modeling); this attempt is in line with the further understanding of the model features, especially in the considered domain, characterized by a complex orography as well as an almost equally partitioned land–sea surface area. An extraordinary number of 24 model parameters have been tested for the whole 2020 year in reference to 88 Greek meteorological stations, with regard to the standard synoptic meteorological variables of 2 m temperature, 2 m minimum and maximum temperatures, dew-point temperature, 10 m wind intensity and 12 h accumulated precipitation. For these variables, the model sensitivity is given in terms of the annual average of all stations for the fifth lead day of the model runs when the sensitivity is expected to reach its peak. It was found that there is a considerable impact regarding the minimum and maximum values for many of the examined parameters in reference to their default values, and consideration is given to a heuristic recommendation on the selection of the most sensitive parameters.

Extreme weather events are identified as a major area of interest, and further consideration is demanded. This study investigates the synoptic and dynamic aspects of a storm system, named “Athina”, that affected most of Greece in early October 2021. This system is synoptically attributed to a low surface pressure generated in the Gulf of Genoa, linked to a mid-tropospheric, almost neutral tilted trough, over central Europe. “Athina” brought heavy rain and strong winds to many parts of Greece, causing flooding and landslides in several areas and caused travel disruptions, with ferries and flights cancelled due to the adverse weather conditions. The worst-hit regions were the northwestern part of the country and Evia. Synoptic maps for upper and lower troposphere, observations from Hellenic National Meteorological Service’s network, and satellite imagery were usedfor the analysis of this weather event. The results from a regional numerical weather prediction model are also presented.

The sensitivity of the ICON model is gauged towards the establishment of ICON-LEPS in place of the currently operational COSMO-LEPS. A broad list of the model’s parameters were tested over a domain covering the wider area of Greece and Italy in the year 2020. ICON model runs were performed on a 6.5 km horizontal grid and were enforced by the ECMWF operational forecast in 3 h intervals. The model’s sensitivities were applied to several surface meteorological fields via their areal averages in the last (132nd) lead time hour of the model runs, when they were expected to be at their climax. It was found that there was a considerable impact regarding the minimum and maximum values for many of the examined parameters in reference to their default values, providing a valuable insight into the understanding of the ICON model in reference to previous works regarding the COSMO model. In addition, due to the extensive forecast period, a seasonal dependence with respect to the considered meteorological fields was displayed. These features are expected to be of major importance in deciding the most important parameters for the application of perturbation techniques in the ensemble process and methodology.

The limited availability of wind profile measurements has hindered atmospheric models and climate systems’ understanding. The European Space Agency’s Aeolus mission’s space-based Doppler wind lidar technology could solve this issue by measuring wind profiles in Near-Real-Time, providing valuable data for Numerical Weather Prediction (NWP) models. A case study using the COSMO NWP model demonstrates the potential of Aeolus data in improving NWP models by examining the impact of Medicane IANOS in September 2020 over the Thessaly plain. The study aims to improve our ability to predict severe weather events and advance our understanding of Earth’s atmosphere.

The objective calibration method originally performed on regional climate models is applied to a fine horizontal resolution Numerical Weather Prediction (NWP) model over a mainly continental domain covering the Alpine Arc. The method was implemented on the MeteoSwiss COSMO (consortium for a small-scale modeling) model with a resolution of 0.01° (approximately 1 km). For the model calibration, five tuning parameters of the parameterization schemes affecting turbulence, soil-surface exchange and radiation were chosen. A full year was simulated, with the history of the soil included (hindcast) to find the optimal parameter value. A different year has been used to give an independent assessment of the impact of the optimization process. Although the operational MeteoSwiss model is already a well-tuned configuration, the results showed that a slight model performance gain is obtained by using the Calibration of COSMO (CALMO) methodology.