USE OF MULTIMODEL SUPERENSEMBLE TECHNIQUE FOR MOUNTAIN-AREA WEATHER FORECAST IN THE OLYMPIC AREA OF TORINO 2006

The XX Olympic Winter Games will be held in Torino, Italy, on February 10-26, 2006 and the IX Paralympic Winter Games on March 10-19, 2006. The Olympic mountain venues are set in middle-, high- and very high-mountain places in the Susa and Chisone Valleys in Piedmont (up to 2600 m above sea level), therefore weather forecasts are strongly dependent on the complex geography and orography of these valleys. Direct model outputs, even from high-resolution limited area models, show many strong systematic and random errors in the forecast, compared to the values observed by our high-density non-GTS network. We present some results of the Multimodel SuperEnsemble technique (Krishnamurti et al. 2000) applied on both global circulation models and on nonhydrostatic limited-area models. The Multimodel SuperEnsemble technique takes into account various model outputs, weighted by parameters calculated in a training period. This is one of the first applications of this technique with limited-area models and in a narrow mountain area and results show a good improvement of meteorological parameter forecasts such as temperature and precipitation

USE OF MULTIMODEL SUPERENSEMBLE TECHNIQUE FOR MOUNTAIN-AREA WEATHER FORECAST IN THE OLYMPIC AREA OF TORINO 2006

The XX Olympic Winter Games will be held in Torino, Italy, on February 10-26, 2006 and the IX Paralympic Winter Games on March 10-19, 2006. The Olympic mountain venues are set in middle-, high- and very high-mountain places in the Susa and Chisone Valleys in Piedmont (up to 2600 m above sea level), therefore weather forecasts are strongly dependent on the complex geography and orography of these valleys. Direct model outputs, even from high-resolution limited area models, show many strong systematic and random errors in the forecast, compared to the values observed by our high-density non-GTS network. We present some results of the Multimodel SuperEnsemble technique (Krishnamurti et al. 2000) applied on both global circulation models and on nonhydrostatic limited-area models. The Multimodel SuperEnsemble technique takes into account various model outputs, weighted by parameters calculated in a training period. This is one of the first applications of this technique with limited-area models and in a narrow mountain area and results show a good improvement of meteorological parameter forecasts such as temperature and precipitation

Impact of different external parameters on Turin UHI with COSMO at 1km

In an increasingly urbanized world, the numerical weather prediction models need to better represent the urban areas, in order to capture the micro-climate phenomena induced by the cities. The parameterization TERRA_URB (TU) (Wouters et al., 2016), recently implemented in COSMO (Bucchignani et al., 2019), not only represents a novelty in this field but has proved to correctly reproduce the Urban Heat Island effect over different European cities (Garbero et al., 2021). TU provides a heterogeneous description of the urban-atmosphere interactions, through the definition of several urban external parameters, such as the anthropogenic heat flux (AHF), the impervious surface area fraction (ISA), and other urban canopy parameters such as the building area fraction (BF), the mean building height (H) and the height-to-width ratio (H/W). In this study we performed simulations with COSMO model at 1 km resolution with the aim of a better characterization of the UHI over the city of Turin. In particular, we compared the results by using AHF and ISA from the EXTPAR preprocessor and from the Local Climate Zones (LCZ) classification system (Stewart and Oke, 2012). Furthermore, we focused on the influence of the urban parameters BF, H and H/W by comparing two different approaches: as a default, their values are assumed constant for all the urban grid points, while a different 2-D approach consists in deriving their values for each urban grid point based on LCZ classification (Demuzere et al., 2019). A sensitivity analysis was then performed to detect which of the 2-D urban parameters have a greater impact on the results, with an emphasis on the Surface Energy Balance (SEB). With the purpose of unravelling the driving mechanism behind the UHI, we analyzed the individual SEB components and evaluated how much each flux contribute to the urban heat island effect

An innovative approach to select urban-rural sites for Urban Heat Island analysis: the case of Turin (Italy)

A novel metric – the Mean Temperature Difference (MTD) – is proposed for the selection of urban-rural pairs of stations needed in the Urban Heat Island (UHI) quantification. This metric highlights the thermal pattern typical of each weather station with respect to the average one of the area of interest. Afterwards, Principal Component Analysis is adopted to cluster stations into subsets exhibiting similar thermal behaviors. The joint use of MTD and PCA allows one to classify stations objectively and without the need of preliminary assumptions about the station landscapes. An application to the metropolitan area of Turin (Italy) and a comparison with validated methods to select urban-rural pairs demonstrate that the proposed approach is easily interpretable and reliable also when the study area exhibits a non-trivial landscape categorization

Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities

The increase in built surfaces constitutes the main reason for the formation of the Urban Heat Island (UHI), that is a metropolitan area significantly warmer than its surrounding rural areas. The urban heat islands and other urban-induced climate feedbacks may amplify heat stress and urban flooding under climate change and therefore to predict them correctly has become essential. Currently in the COSMO model, cities are represented by natural land surfaces with an increased surface roughness length and a reduced vegetation cover, but this approach is unable to correctly reproduce the UHI effect. By increasing the model resolution, a representation of the main physical processes that characterize the urban local meteorology should be addressed, in order to better forecast temperature, moisture and precipitation in urban environments. Within the COSMO Consortium a bulk parameterization scheme (TERRA_URB or TU) has been developed. It parametrizes the effects of buildings, streets and other man-made impervious surfaces on energy, moist and momentum exchanges between the surface and atmosphere, and additionally accounts for the anthropogenic heat flux as a heat source from the surface to the atmosphere. TU implements an impervious water-storage parameterization, and the Semi-empirical Urban canopy parametrization (SURY) that translates 3D urban canopy into bulk parameters. This paper presents evaluation results of the TU scheme in high-resolution simulations with a recent COSMO model version for selected European cities, namely Turin, Naples and Moscow. The key conclusion of the work is that the TU scheme in the COSMO model reasonably reproduces UHI effect and improves air temperature forecasts for all the investigated urban areas, despite each city has very different morphological characteristics. Our results highlight potential benefits of a new turbulence scheme and the representation of skin-layer temperature (for vegetation) in the model performance. Our model framework provides perspectives for enhancing urban climate modelling, although further investigations in improving model parametrizations, calibration and the use of more realistic urban canopy parameters are needed

Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

Effective and time-efficient aircraft assistance and guidance in severe weather environments remains a challenge for air traffic control. Air navigation service providers around the globe could greatly benefit from specific and adapted meteorological information for the controller position, helping to reduce the increased workload induced by adverse weather. The present work proposes a radar-based nowcasting algorithm providing compact meteorological information on convective weather near airports for introduction into the algorithms intended to assist in air-traffic management. The use of vertically integrated liquid density enables extremely rapid identification and short-term prediction of convective regions that should not be traversed by aircraft, which is an essential requirement for use in tactical controller support systems. The proposed tracking and nowcasting method facilitates the anticipation of the meteorological situation around an airport. Nowcasts of centroid locations of various approaching thunderstorms were compared with corresponding radar data, and centroid distances between nowcasted and observed storms were computed. The results were analyzed with Method for the Object-Based Evaluation from the Model Evaluation tools software (MET-10.0.1, Developmental Testbed Center, Boulder, CO, US) and later integrated into an assistance arrival manager software, showing the potential of this approach for automatic air traffic assistance in adverse weather scenarios

Is an NWP-Based Nowcasting System Suitable for Aviation Operations?

The growth of air transport demand expected over the next decades, along with the increasing frequency and intensity of extreme weather events, such as heavy rainfalls and severe storms due to climate change, will pose a tough challenge for air traffic management systems, with implications for flight safety, delays and passengers. In this context, the Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM (SINOPTICA) project has a dual aim, first to investigate if very short-range high-resolution weather forecast, including data assimilation, can improve the predictive capability of these events, and then to understand if such forecasts can be suitable for air traffic management purposes. The intense squall line that affected Malpensa, the major airport by passenger traffic in northern Italy, on 11 May 2019 is selected as a benchmark. Several numerical experiments are performed with a Weather Research and Forecasting (WRF) model using two assimilation techniques, 3D-Var in WRF Data Assimilation (WRFDA) system and a nudging scheme for lightning, in order to improve the forecast accuracy and to evaluate the impact of assimilated different datasets. To evaluate the numerical simulations performance, three different verification approaches, object-based, fuzzy and qualitative, are used. The results suggest that the assimilation of lightning data plays a key role in triggering the convective cells, improving both location and timing. Moreover, the numerical weather prediction (NWP)-based nowcasting system is able to produce reliable forecasts at high spatial and temporal resolution. The timing was found to be suitable for helping Air Traffic Management (ATM) operators to compute alternative landing trajectories

Forecasting the weather to assist ATC and ATM operations

In EUROCONTROLS's recent summary report on Climate Changes Risks for European Aviation, several weather-related impacts were highlighted. There is a strong relation between highly impacting weather events and disruptions to the aviation network resulting in additional fuel consumption and CO2 emissions. In Europe, severe weather is responsible for up to 7.5% of the total en-route delays. In this respect, the H2020 Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM (SINOPTICA) project aims to demonstrate that very high-resolution and very short-range numerical weather forecasts, benefiting from the assimilation of radar data, in-situ weather stations, GNSS and lightning data, can improve the prediction of extreme weather events to the benefit of Air Traffic Management (ATM) and Air Traffic Control (ATC) operations. The assimilation of radar, GNSS, and lightning data shows a positive impact on the forecast of the convective cells for the four selected severe weather events. Moreover, two radar-based nowcasting strategies, PhaSt and RaNDeVIL, are tested to predict storm structures. Both methods are able to follow the more intense cells (VIL > 10 kg/m2) in all the case studies, as shown by the MODE results and the eye-ball verification The forecasts are used in an arrival management system (AMAN) to compute 4D trajectories around convective areas, integrate the affected aircraft into the arrival sequence, and assist air traffic controllers in implementing the approaches through just in time advisories and dynamic weather displays. With the help of real traffic scenarios and different weather models, diverse approach planning strategies are evaluated