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- ItemInitial phase of the Hans-Ertel Centre for Weather Research - A virtual centre at the interface of basic and applied weather and climate research(Stuttgart : Schweizerbart, 2014) Weissmann, Martin; Göber, Martin; Hohenegger, Cathy; Janjic, Tijana; Keller, Jan; Ohlwein, Christian; Seifert, Axel; Trömel, Silke; Ulbrich, Thorsten; Wapler, Kathrin; Bollmeyer, Christoph; Deneke, HartwigThe Hans-Ertel Centre for Weather Research is a network of German universities, research institutes and the German Weather Service (Deutscher Wetterdienst, DWD). It has been established to trigger and intensify basic research and education on weather forecasting and climate monitoring. The performed research ranges from nowcasting and short-term weather forecasting to convective-scale data assimilation, the development of parameterizations for numerical weather prediction models, climate monitoring and the communication and use of forecast information. Scientific findings from the network contribute to better understanding of the life-cycle of shallow and deep convection, representation of uncertainty in ensemble systems, effects of unresolved variability, regional climate variability, perception of forecasts and vulnerability of society. Concrete developments within the research network include dual observation-microphysics composites, satellite forward operators, tools to estimate observation impact, cloud and precipitation system tracking algorithms, large-eddy-simulations, a regional reanalysis and a probabilistic forecast test product. Within three years, the network has triggered a number of activities that include the training and education of young scientists besides the centre's core objective of complementing DWD's internal research with relevant basic research at universities and research institutes. The long term goal is to develop a self-sustaining research network that continues the close collaboration with DWD and the national and international research community.
- ItemStatus and future of numerical atmospheric aerosol prediction with a focus on data requirements(Katlenburg-Lindau : EGU, 2018) Benedetti, Angela; Reid, Jeffrey S.; Knippertz, Peter; Marsham, John H.; Di Giuseppe, Francesca; Rémy, Samuel; Basart, Sara; Boucher, Olivier; Brooks, Ian M.; Menut, Laurent; Mona, Lucia; Laj, Paolo; Pappalardo, Gelsomina; Wiedensohler, Alfred; Baklanov, Alexander; Brooks, Malcolm; Colarco, Peter R.; Cuevas, Emilio; da Silva, Arlindo; Escribano, Jeronimo; Flemming, Johannes; Huneeus, Nicolas; Jorba, Oriol; Kazadzis, Stelios; Kinne, Stefan; Popp, Thomas; Quinn, Patricia K.; Sekiyama, Thomas T.; Tanaka, Taichu; Terradellas, EnricNumerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol-climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term "requirements" is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of "bin" and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.