Peter Mieth

Chemical effects in 11-year solar cycle simulations with the freie universitat Berlin climate middle atmosphere model with online chemistry (FUB-CMAM-CHEM)

The impact of 11-year solar cycle variations on stratospheric ozone (O3) is studied with the Freie Universitat Berlin Climate Middle Atmosphere Model with interactive chemistry (FUB-CMAM-CHEM). To consider the effect of variations in charged particle precipitation we included an idealized NO x source in the upper mesosphere representing relativistic electron precipitation (REP). Our results suggest that the NO x source by particles and its transport from the mesosphere to the stratosphere in the polar vortex are important for the solar signal in stratospheric O3. We find a positive dipole O3 signal in the annual mean, peaking at 40–45 km at high latitudes and a negative O3 signal in the tropical lower stratosphere. This is similar to observations, but enhanced due to the idealized NO x source and at a lower altitude compared to the observed minimum. Our results imply that this negative O3 signal arises partly via chemical effects.

Chemical reaction pathways affecting stratospheric and mesospheric ozone

Catalytic cycles and other chemical pathways affecting ozone are normally estimated empirically in atmospheric models. In this work we have automatically quantified such processes by applying a newly developed analysis package called the Pathway Analysis Program (PAP). It used modeled chemical rates and concentrations as input. These were supplied by the Module Efficiently Calculating the Chemistry of the Atmosphere MECCA box model, itself initialized by the Free University of Berlin Climate Middle Atmosphere Model with Chemistry. We analyzed equatorial, midlatitude and high-latitude locations over 24-hour periods during spring in both hemispheres. We present results for locations in the lower stratosphere, upper stratosphere and midmesosphere. Oxygen photolysis dominated (>99%) in situ ozone production in the equatorial lower stratosphere, in the upper stratosphere and in the mesosphere. In the lower stratosphere midlatitudes the ozone smog cycle (already established in the troposphere) rivaled oxygen photolysis as an in situ ozone source in both hemispheres. However, absolute ozone production rates in midlatitudes were rather slow compared with at the equator, typically 1650 ppt ozone/day. In the equatorial lower stratosphere, five catalytic sinks were important (each contributing at least 5% to chemical ozone loss): a HOx cycle, a HOBr cycle and its HOCl analog, a water-HOx cycle and a mixed chlorine-bromine cycle. Important in midlatitudes were the HOx cycle, a NOx cycle, the HOBr cycle and the mixed chlorine-bromine cycle. In lower-stratosphere high latitudes, the chlorine dimer cycle and the mixed chlorine-bromine cycle dominated in both hemispheres. A variant on the latter, involving BrCl formation, also featured. In the upper stratosphere high latitudes (where strong negative ozone trends are observed), a nitrogen cycle, a chlorine cycle, and a mixed chlorine-nitrogen cycle were found. In the mesosphere, three closely related HOx cycles dominated ozone loss.

Scalable Generation of Synthetic GPS Traces with Real-Life Data Characteristics

Database benchmarking is most valuable if real-life data and workloads are available. However, real-life data (and workloads) are often not publicly available due to IPR constraints or privacy concerns. And even if available, they are often limited regarding scalability and variability of data characteristics. On the other hand, while easily scalable, synthetically generated data often fail to adequately reflect real-life data characteristics. While there are well established synthetic benchmarks and data generators for, e.g., business data (TPC-C, TPC-H), there is no such up-to-date data generator, let alone benchmark, for spatiotemporal and/or moving objects data.

The DYMOS Model System for the Analysis and Simulation of Regional Air Pollution

The paper presents results of the development and application of an air pollution simulation system at GMD FIRST which aims to support users in governmental administration and industry with forecasting and operative decision-making as well as short to long-term regional planning. The components of the simulation system are parallelly implemented simulation models for meteorology, transport and air chemistry, data bases for model input and simulation results, as well as a graphic user interface for spatial data visualization. Results will be presented from two recent applications in the regions of Berlin/Brandenburg and Munich (Germany).

Using the Road Traffic Simulation “SUMO” for Educational Purposes

Since the year 2000, the Centre of Applied Informatics and the Institute for Transport Research at the German Aerospace Centre develops a microscopic road traffic simulation package named ’SUMO’ — an acronym for “Simulation of Urban MObility”. Meanwhile, the simulation is capable to deal with realistic scenarios such as large cities and is used for these purposes within the institutes projects. The idea was to support the traffic research community with a common platform to test new ideas and models without the need to reimplement a framework that handles road data, vehicle routes, traffic light steering etc. To achieve this goal, the simulation code is available as open source. Within this publication, we would like to demonstrate how most attributes of traffic flow can be simulated. This should be mainly interesting for educational purposes.

Simulation of traffic-induced air pollution for mesoscale applications

Recent investigations have shown that vehicular traffic is the main source for emissions leading to summer smog. A study of the impact of traffic emission on urban air quality requires a complex air-pollution simulation system. This paper presents results of the development and application of an air-pollution simulation system at GMD FIRST which aims at supporting users in government administration and industry with forecasting and operative decision-making as well as short- to long-term regional planning. The components of the simulation system are parallelly implemented simulation models for meteorology, transport and air chemistry, data bases for model input and simulation results, as well as a graphic user interface for spatial data visualization. In order to study the influence of traffic emissions, a traffic-flow and a traffic-emission model have been added to the simulation system. Results presented are from two recent applications in the regions of Berlin/Brandenburg and Munich (Germany). Further applications are in preparation.

Simulation of air pollutant dispersion on parallel hardware

Abstract This paper deals with the analysis and simulation of air pollutant dispersion in the region of Berlin. Results from simulations of a winter smog episode are presented. A concept of a simulation package for summer smog consisting of a complex meteorological model, an air chemistry model, and a dynamic model of emissions for data input is described. It is pointed out that a system of such numerical models is very complex. Simulation runs and scenario analyses take hours of computing time, even on todays supercomputers. Therefore a strategy for model decomposition and implementation on massively parallel computers is described. As an example this is carried out on one particular atmospheric model.

Simulation tool for space borne traffic data collection

Space borne traffic data collection is an important method to complement surface and air borne data. We present a first version of a simulation tool that analyses the feasibility of detection of traffic situation over large areas using radar sensors on satellites and airplanes. With this tool it will be possible to evaluate the information content of traffic data acquired by any given sensor. In this tool, the processes determining traffic data collection with space borne radar sensors are reconstructed. All relevant features for traffic monitoring, starting with the traffic scene followed by the sensor and traffic data extraction and interpretation, are simulated. The simulation tool has a modular structure. Each module is independent and exchangeable and describes one separate part of the traffic remote sensing process. The modular structure of the software guarantees maximum flexibility and portability. Changes in one module do not necessarily require changes in other modules. This tool is suitable for a precise specification and optimization of sensor and satellite parameters for traffic data collection. The results can be applied to future satellite missions.