Invited Speakers

Georgios Amanatidis

Albert Ansmann

Sasha Madronich

Silas Michaelides

Vlado Spiridonov

Christos. S. Zerefos

 

 

Georgios Amanatidis

European Parliament, Directorate-General for Internal Policies of the Union,

Secretariat of the Committee on the Environment, Public Health and Food Safety

Rue Wiertz 60, SQM 10Y13, 1047 Brussels, Belgium

European climate change policies and research in coherence with the 2015 Paris Agreement

Over the last two decades, the overarching objective of EU climate policy has been to limit global warming to 2°C above pre-industrial average temperature levels. In this regard, the EU is already committed to reducing its greenhouse gas emissions by at least 20% below 1990 levels by 2020, while improving energy efficiency by 20% and increasing the share of renewable energy sources to 20%. In October 2014, the EU's Climate and Energy Policy Framework for 2030 was adopted with a greenhouse gas emission reduction target of at least 40% compared to 1990, while it also sets the target of at least 27% for both renewable energy and energy efficiency. These 2030 targets were the basis for the EU's position ahead of the international climate negotiations which took place in Paris in December 2015, where a global climate agreement was reached. In parallel, the EU budget for low carbon related research under Horizon 2020 Programme for Research and Innovation has already effectively been doubled for the period 2014-2020, and the EU has committed to invest at least 35% of Horizon 2020 into climate-related activities. This presentation describes European climate change policies and research in coherence with the Paris Agreement and the challenges ahead to ensure the achievement of the Paris Agreement goal of keeping global warming well below 2°C and pursuing efforts towards 1.5°C.

 

Albert Ansmann

Leibniz Institute for Tropospheric Research, Permoserstr. 15, 04316 Leipzig, Germany.

Advances in understanding of aerosol-cloud-dynamics relationships: the role of active (lidar/radar) remote sensing

For an improved understanding of cloud evolution, cloud life cycle,  formation of precipitation, and the specific impact of aerosol (pollution) on cloud processes comprehensive observational efforts are needed. Compared to all  alternative approaches to study aerosol-cloud interaction,  only ground-based active remote sensing with Doppler lidar, cloud radar, aerosol Raman/polarization lidar and wind profiler permits continuous monitoring of cloud developments in their natural aerosol environment at given updraft/downdraft/mixing/entrainment characteristics with high vertical and temporal resolution. Cloud profiling, simultaneously from base to top, is required which cannot be realized by means of airborne in situ observations. In this presentation the latest methodological and technical developments in the field of lidar and combined lidar/radar/profiler applications will be presented. Measurements will be shown. Especially in the field of aerosol retrievals (lidar-based retrieval of dust and non-dust aerosol components and profiles of cloud condensation nucleus and ice-nucleating particle number concentrations) and vertical-wind-component characterization in and around cloud layers, significant progress has been made during the last few years. European network (ACTRIS/EARLINET/CLOUDNET) activities foster the study of aerosol-cloud interaction on the European scale. In September 2016, a modern remote sensing CLOUDNET station will be setup in the Eastern Mediterranean (Limassol, Cyprus, 2016-2017). This region can be regarded as a unique natural laboratory with unique aerosol conditions (mixtures of desert dust, biomass burning smoke, urban haze, and marine aerosols) and related aerosol-cloud interactions.

 

Sasha Madronich

National Center for Atmospheric Research, Boulder, Colorado USA

Rapid Growth and Decay of Tropospheric Secondary Organic Aerosols

Hydrocarbons react in the atmosphere to generate partly oxygenated organic compounds, many of which have low vapor pressures and therefore condense easily to form fine particles. These organic aerosols affect atmospheric visibility, radiative forcing of climate, cloud nucleation, photochemical actinic fluxes, as well as human health. Yet large uncertainties still exist about their formation, properties, and removal. Many different hydrocarbons can contribute, each with its own chemical details. We have developed a detailed chemical model (the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere, GECKO-A) to represent the photo-oxidation of hydrocarbons and their products, based on laboratory data when available and structure-activity relations when not. These data are managed by a computer code, allowing estimation of kinetic, thermodynamic, and optical parameters for hundreds of hydrocarbons and many thousand intermediates spawned by their atmospheric degradation (aldehydes, ketones, alcohols, organic nitrates, peroxides, acids, etc.). This explicit chemical detail has allowed unprecedented insights into the condensational growth of organic particles, as well as exploration of alternate removal processes including rainout, dry deposition, oxidation of the particle surface, and photolysis. Comparisons of the model with observations from smog chambers and field campaigns are encouraging. Results suggest that organic particles of urban origin may continue to grow for several days downwind of the source – something that is not currently well represented in regional and global air quality and climate models.  We also find more rapid losses than assumed in current models, by dry deposition of the gas/particle system, and by photolysis at ultraviolet wavelengths.

 

Silas Michaelides

Director of Cyprus Department of Meteorology

Artificial Neural Networks: a nonlinear tool for applications in Meteorology and Climatology

The huge advancements made in Atmospheric Sciences during the last decades are unequivocal, promoted primarily by the broadening of our understanding of the underlying mechanisms with inputs from a large number of scientific disciplines, such as Physics, Chemistry, Mathematics. In addition to the enhancements made in our knowledge about the physical mechanisms, this progress was also due to the availability of massive data resources and the swift technological advancements. Part of this expansion of our understanding of the atmospheric system is also due to the introduction of new methodologies for non-deterministic analysis, beyond the traditional statistical ones. The Earth's atmosphere, including its weather related and climate components comprise an intrinsically nonlinear physical system. Indeed, nonlinearity is a prime characteristic of most of the issues related to the atmospheric sciences. The search for methodologies to tackle this nonlinear character of atmospheric problems, has led to the exploitation of several suitable approaches. One such approach which appears to have great potential in dealing with atmospheric related problems is neural computation or as it is widely known the Artificial Neural Networks methodology. Although Artificial Neural Networks were introduced in the 1940's, the first application related to Atmospheric Sciences appeared twenty years later followed by a long inactive period. Another twenty years elapsed for this new technology to be explored more extensively in atmospheric sciences. The late exploitation of Artificial Neural Networks in Atmospheric Sciences can be attributed to a number of reasons which are associated with their historical evolution but also to the perception that many scientists had for ANN. For example, some researchers have dismissed neural networks as uninformative black boxes with limited explanatory power, in the absence of an underlying statistical model. This unfairly acquired reputation is not necessarily justified, as there are techniques available to interpret the function represented by the respective Artificial Neural Network model. Today, Artificial Neural Networks have reached a sufficient level of maturity regarding atmospheric-related applications. Compared to the limited research that existed twenty years ago, the number of published papers, books, reports and conference proceedings overshadows this notable lack of early interest. Artificial Neural Networks have established themselves as advantageous full-fledged scientific tools that can be used effectively in a wide range of topics encountered in Atmospheric Sciences. Selected applications will demonstrate this advantage.

 

Vlado Spiridonov

Permanent Representative of WMO Commission of Atmospheric Sciences

Former director of Hydrometeorological Service

St. Cyril & Methodius University, Faculty of Natural Sciences and Mathematics, Institute of Physics-Meteorology, Skopje

Αdvanced tools to forecast extreme convective weather

Convective storms are perhaps the most violent of all storm types, and are capable of producing damaging winds, large amounts of hail, heavy rainfall and weak-to-violent tornadoes. An important aspect in the study of convective clouds is the identification of some processes as cloud splitting or merging, which lead to intense hailfall and rainfall. These processes are found to depend on the atmospheric stability, wind shear and veering, the relative stages of development of the two clouds and their initial separation. Interaction between convective cells may alter cell longevity, intensity, and propagation characteristics. Convective cloud systems are also significant from a climatological point of view. The forecast of such atmospheric phenomena is still a big challenge due to complexity of the processes which are on the sub-scale domain of mesoscale models and also considering the fact that the finite amount of computing power makes it difficult to model at adequate resolution for this phenomena. Convective scale numerical weather prediction becomes increasingly important in forecast of a small-scale atmospheric processes. The non-hydrostatic mesoscale numerical models, running with fine grid resolution and explicit resolving of moist convection-thereby avoiding cumulus parameterization have been extensively used to forecast such extreme weather events. Despite the positive results in respect to accurate forecast of structure of these system and distribution of convective rainfall, there are still some uncertainties in more detail forecast of small scale convective features (e.g. timing, location and intensity of heavy convective rainfall). A three dimensional cloud model represents a valuable tool for a more detailed representation of the convective scale processes and improvement of our understanding concerning the processes important in the initiation and development of the severe storms as well as which factors contributed to the associated heavy rainfall. Such advanced tool based on WRF model coupled with a cloud resolving model has been employed to examine disastrous convective case that hit Skopje on 6 August 2016 and caused flash-flooding with catastrophic consequences. According to the official sources, 23 people lost their lives during this disastrous heavy rainfall event which also caused huge material and economy damages. The obtained results imply on occurrence supercell storm with mesocyclone. The main triggering factors for heavy rainfall and flash flooding are: development of the specific storm dynamics, enhanced rotating updrafts compensated with downdrafts, powerful thunderstorm with longer life cycle than usual, large production of rainwater, extreme rainfall intensity. The catastrophic storm that hit Skopje city was unusual for mid-latitude areas and had characteristics typical for a tropical storm. The maximum overshooting top was extended up to 15 km. The maximum vertical speed of 100 km/hr and horizontal speed of about 115 km/h. The total accumulated rainfall was 123 mm for 60 min simulation time, the averaged rate of three successive peak rainfalls was 38mm/5min, fallout in a localized area of 10-15 km2. Three-dimensional simulation gives a realistic picture of the nature and severity of this rare destructive weather phenomenon. This novel scientific method showed a good potential and ability to improve our knowledge and understanding of the physical processes related to such severe convective clouds and the main ingredients responsible for development of this supercell storm with mesocyclone which hit the city of Skopje and the surrounding area and caused people loses and significant material damages.

 

Christos. S. Zerefos

Professor Emeritus, Academician

From Aristotle, the founder of atmospheric science, to Copernicus Atmospheric Services 2020

2016 is declared as Aristotle's year, the person who first defined the term «climate» from the inclination of Sun rays, and also the year during which the first results of the Copernicus Atmospheric Service will be published. The lecture will start with the history of climatology introduced with Aristotle's work «Meteorology» and continue with the interpretation of physical phenomena during the 18th century, when the contemporary science of meteorology and climatology was founded and yielded significant advancements.  The developments in the field of atmospheric science will be presented, including philosophical aspects of climate and description of current atmospheric services, which allow assimilation and forecasting of atmospheric composition.