This study analyses characteristics of deep moist convection (DMC) over Germany with the aim to select relevant parameters that have the skill to improve the identification of current life cycle phase and the forecast of a lifetime of DMCs in an operational weather forecasting environment.No differentiation between thunderstorm organization types is done, since no simple differentiation method is available in an operational environment.In contrast to previous analyses, multiple data sources are used synchronously to explore an extensive data set of DMCs at high resolution in space and time.Basis of our analysis are all DMC detections in satellite data (using Cb-TRAM -Thunderstorm Tracking and Monitoring) in a five month period (June 2016, May/June/July 2017, and June 2018).For each of these DMCs the time series of selected parameters from satellite, ground-based radar, lightning detection, and numerical weather prediction (NWP) model data are inspected.In search for clear signatures of expectable lifetime and differences between shortand long-lived DMCs, all thunderstorm systems are sorted by their lifetime.In addition, they are separated into four life cycle phases: 1. early growth, 2. advanced growth, 3. maturity, and 4. decay.Generally, it turns out that satellite, radar, and lightning data are the most suitable data to determine the actual life cycle phase of a DMC.It is shown that long-lived DMCs are, on average, related to lower minimum cloud top temperature and mid-level relative humidity and higher maximum of coverage area, vertically integrated water and lightning activity during their life cycle than short-lived systems.The NWP model parameters have a diagnostic potential to identify the remaining lifetime in connection with the observational data, but do not contain information about the actual life cycle phase.The results obtained in this study will be used for an investigation of their potential application in a nowcasting model, in order to determine the current phase of an observed DMC and to predict its remaining lifetime.

Aviation is heavily affected by thunderstorms. Approaching storm cells with accompanying effects such as heavy rain, hail or downdrafts cause delays and flight cancellations. Consequently, the airlines and airport operators have to bear high additional costs, with reduced flight safety and passenger comfort. A reliable thunderstorm forecast up to several hours ahead saves time for decision makers, as the airport authorities, air traffic control, airline operation centre, and the crew in the cockpit for an appropriate and harmonised reaction, and for mitigating the consequences of a thunderstorm. The algorithm Cb-LIKE (Cumulonimbus-Likelihood) has been developed to provide such forecasts. Cb-LIKE is an automated system which designates areas with possible thunderstorm development by using output of the COSMO-DE numerical weather prediction model operated by the German Meteorological Service (DWD). The algorithm includes a newly developed "Best-Member-Selection" which allows the automatic selection of that member of a COSMO-DE ensemble that matches best with the current weather situation. An innovative fuzzy logic system combines selected model data and calculates a thunderstorm indicator for each grid point of the model domain for the following six hours in one hour intervals. Comparing thunderstorm observations by radar with Cb-LIKE forecasts in the summer period of 2012 verifies the algorithm and demonstrates the system's performance. The verification shows that Cb-LIKE gives better thunderstorm forecasts in comparison with the COSMO-DE radar reflectivity. Moreover, the verification results allow transformation of the Cb-LIKE indicator field into a field of thunderstorm probability. These probability forecasts are valid for thunderstorms within a certain spatial distance from the observed storms.

The added value of a satellite-based thunderstorm detection and nowcasting system with respect to flight safety and efficiency is shown by comparing onboard observations carried out by Deutsche Lufthansa AG and Deutsches Zentrum für Luft- und Raumfahrt pilots to the detection and nowcasting information in both postflight analyses and in real time. For the first time, detection and nowcasting data could be successfully uplinked into the cockpit of aircraft during flight in real time, thereby demonstrating that these data are in good agreement with the returns of the onboard radar, and furthermore provide an overview of the thunderstorm situation around the aircraft and along the aircraft’s flight track. Pilots can use the detection and nowcasting information to strategically plan their route up to 1 h ahead in time. The result is safer flight routes that avoid inadvertent flights through areas where thunderstorm-related hazards like turbulence, icing, and hail occur. In addition, the improved strategic planning enables smarter flight routes, resulting in fuel savings, reduced delays, and less deviations to alternates.

Winterliche Wetterbedingungen an Flughafen haben masgeblichen Einfluss auf die Punktlichkeit, die Effizienz und letztendlich auch die Sicherheit des Luftverkehrs. Um den okonomischen Schaden in lichen Situationen zu minimieren und die Sicherheit zu gewahrleisten ist es notig, die Winterwetterverhaltnisse in der Terminal Manoeuvring Area (TMA) um den Flughaven so prazise wie moglich zu erfassen und vorherzusagen. Vor allem die Niederschlagsart und Menge sowie der zeitliche Ablauf sind fur Flughafenbetreiber wie auch fur Strasenbetriebsdienst elementare Informateionen.

The operators of the business and regional aviation in Europe would strongly benefit from inflight weather forecasting and trajectory tracking in order to fly safely and to optimise the trajectory. On the other hand, weather agencies would greatly benefit from weather observations provided by regional and business aviation (e.g. temperature and wind speed data collected by the aircraft sensors, nowadays delivered only by commercial airlines in the framework of AMDAR) as they would drastically increase geographical coverage and number of measurement thanks to different routes w.r.t. commercial airlines. Near-real-time in-flight weather services for business and regional aviation are nowadays quite well developed in USA, but still very limited in Europe due to the lack of equivalent infrastructure and service offer. Thus, the PLANET-2 project, co-funded by the European Space Agency (ESA) and led by ATMOSPHERE-F (F) with ATMOSPHERE-D (G), DLR (G), TRIAGNOSYS (G) and METEO-FRANCE (F), aims at developing a commercially sustainable in-flight weather service based on integrated space assets (i.e. SatCom and Navigation, with the support of Earth Observation data for some of the weather products) and terrestrial wireless networks (e.g. GPRS, 3G, 4G) to reduce service costs. The paper presents the main results of the work carried out to meet the PLANET-2 requirements.

Two limited area model derivatives of the numerical weather prediction model COSMO-DE operated by the German Meteorological Service are introduced. The aim is to obtain frequently updated highly re-solved predictions in a limited area as an aerodrome. The predictions include dynamic parameters as wind and turbulence kinetic energy and thermodynamic quantities as temperature and humidity but also the amount of snow, rain and hail. The models are used in the airport environments of Frankfurt (COSMO-FRA) and Munich (COSMO-MUC) for aircraft wake vortex, thunderstorm activity, and wintry weather warning applications, as detailed in Sections 2.1 to 2.4.

The meteorological network of observation and prediction continuously delivers an enormous amount of various atmospheric parameters. In particular in the area of an aerodrome the observation density is typically higher than on average. In the project we spawned the idea to smartly concatenate the variety of available data which are relevant for aviation and develop new products which use the information contained in the data but describe the phenomenon of interest in a simple and unambiguous way for direct use for the aviation stakeholders. We developed this idea in a concept and related system named WxFUSION, meaning “weather forecast user-oriented system including object nowcasting”.

The successful demonstration and assessment of the DLR thunderstorm nowcasting algorithms at Munich Airport during two campaigns in the summers of 2010 and 2011 are described. The algorithms Cb-TRAM and Rad-TRAM, that detect, monitor, and forecast up to one hour (nowcast) thunderstorm cells from satellite and radar data, run in real time and provided new thunderstorm products for users at the airport. The products were presented on displays the users were already familiar with as well as on webpages designed by DLR. On the webpages, also additional information like measurements with DLR’s polarimetric radar and model forecasts was shown. Moreover, thunderstorm warnings were is-sued and sent via email to the users whenever a thunderstorm was detected in the terminal manoeu-vring area of the airport of Munich. The nowcasting skills of Rad-TRAM and Cb-TRAM are encouraging, especially for lead times up to 30 minutes, and the user feedback on the DLR thunderstorm products was very positive. The Rad-TRAM and Cb-TRAM products provide a good overview on the situation and its future development, and the thunderstorm warnings were very helpful for the collaborative decision making at the airport. However, some suggestions for improvements were made like the demand for nowcasts beyond one hour. This will be considered within the integrated weather forecast system, WxFUSION, which has been further developed during the campaigns.

Recent developments are reported on techniques to determine the onset, duration, amount and type of precipitation as well as the snow and icing conditions at the surface. The algorithms, still under development, will be used to forecast the weather in short to medium lead times, i.e. for the next 30 minutes up to a few hours (“nowcasting”). An algorithm aims at detecting potential areas of snow fall by combining reflectivity data of precipitation and surface temperature data from a numerical model as well as surface stations in high spatial resolution. Another approach combines profiling measurements (e.g., meteo data measured by aircraft and polarimetric radar data) with numerical weather forecast products.

Weather has a significant impact on the safety and efficiency of air traffic during all phases of flight. Especially information on adverse weather must be tailored to the user's needs, easy to understand, self-explaining and clear in its message. DLR-IPA has developed a concept and tools to detect, track and predict hazardous weather elements and provide this information in simple unambiguous form to controllers and pilots. It has been demonstrated that these products make a significant contribution to raising the safety and efficiency of the air transport system.

Airborne lidar and in-situ measurements of aerosols and trace gases were performed in volcanic ash plumes over Europe between Southern Germany and Iceland with the Falcon aircraft during the eruption period of the Eyjafjalla volcano between 19 April and 18 May 2010. Flight planning and measurement analyses were supported by a refined Meteosat ash product and trajectory model analysis. The volcanic ash plume was observed with lidar directly over the volcano and up to a distance of 2700 km downwind, and up to 120 h plume ages. Aged ash layers were between a few 100 m to 3 km deep, occurred between 1 and 7 km altitude, and were typically 100 to 300 km wide. Particles collected by impactors had diameters up to 20 μm diameter, with size and age dependent composition. Ash mass concentrations were derived from optical particle spectrometers for a particle density of 2.6 g cm−3 and various values of the refractive index (RI, real part: 1.59; 3 values for the imaginary part: 0, 0.004 and 0.008). The mass concentrations, effective diameters and related optical properties were compared with ground-based lidar observations. Theoretical considerations of particle sedimentation constrain the particle diameters to those obtained for the lower RI values. The ash mass concentration results have an uncertainty of a factor of two. The maximum ash mass concentration encountered during the 17 flights with 34 ash plume penetrations was below 1 mg m−3. The Falcon flew in ash clouds up to about 0.8 mg m−3 for a few minutes and in an ash cloud with approximately 0.2 mg m−3 mean-concentration for about one hour without engine damage. The ash plumes were rather dry and correlated with considerable CO and SO2 increases and O3 decreases. To first order, ash concentration and SO2 mixing ratio in the plumes decreased by a factor of two within less than a day. In fresh plumes, the SO2 and CO concentration increases were correlated with the ash mass concentration. The ash plumes were often visible slantwise as faint dark layers, even for concentrations below 0.1 mg m−3. The large abundance of volatile Aitken mode particles suggests previous nucleation of sulfuric acid droplets. The effective diameters range between 0.2 and 3 μm with considerable surface and volume contributions from the Aitken and coarse mode aerosol, respectively. The distal ash mass flux on 2 May was of the order of 500 (240–1600) kg s−1. The volcano induced about 10 (2.5–50) Tg of distal ash mass and about 3 (0.6–23) Tg of SO2 during the whole eruption period. The results of the Falcon flights were used to support the responsible agencies in their decisions concerning air traffic in the presence of volcanic ash.