RDM in a Decentralised University Ecosystem—A Case Study of the University of Cologne

The University of Cologne (UoC) has historically grown in highly decentralised structures. This is reflected by a two-layered library structure as well as by a number of decentralised research data management (RDM) activities established on the faculty and research consortium level. With the aim to foster networking, cooperation, and synergies between existing activities, a university-wide RDM will be established. A one-year feasibility study was commissioned by the Rectorate in 2016 and carried out by the department research management, library and computing centre. One study outcome was the adoption of a university-wide research data guideline. Based on a comprehensive RDM service portfolio, measures were developed to put a central RDM into practice. The challenges have been to find the right level of integration and adaptation of existing and established decentralised structures and to develop additional new structures and services. We will report on first steps to map out central RDM practices at the UoC and to develop a structure of cooperation between loosely coupled information infrastructure actors. Central elements of this structure are a competence center, an RDM expert network, a forum for exchange about RDM and associated topics as well as the faculties with their decentralized, domain-specific RDM services. The Cologne Competence Center for Research Data Management (C3RDM) was founded at the end of 2018 and is still in its development phase. It provides a one-stop entry point for all questions regarding RDM. The center itself provides basic and generic RDM services, such as training, consulting, and data publication support, and acts as a hub to the decentral experts, information infrastructure actors, and resources

The HD(CP)² Observational Prototype Experiment (HOPE) – an overview

The HD(CP)2 Observational Prototype Experiment (HOPE) was performed as a major 2-month field experiment in Jülich, Germany, in April and May 2013, followed by a smaller campaign in Melpitz, Germany, in September 2013. HOPE has been designed to provide an observational dataset for a critical evaluation of the new German community atmospheric icosahedral non-hydrostatic (ICON) model at the scale of the model simulations and further to provide information on land-surface–atmospheric boundary layer exchange, cloud and precipitation processes, as well as sub-grid variability and microphysical properties that are subject to parameterizations. HOPE focuses on the onset of clouds and precipitation in the convective atmospheric boundary layer. This paper summarizes the instrument set-ups, the intensive observation periods, and example results from both campaigns. HOPE-Jülich instrumentation included a radio sounding station, 4 Doppler lidars, 4 Raman lidars (3 of them provide temperature, 3 of them water vapour, and all of them particle backscatter data), 1 water vapour differential absorption lidar, 3 cloud radars, 5 microwave radiometers, 3 rain radars, 6 sky imagers, 99 pyranometers, and 5 sun photometers operated at different sites, some of them in synergy. The HOPE-Melpitz campaign combined ground-based remote sensing of aerosols and clouds with helicopter- and balloon-based in situ observations in the atmospheric column and at the surface. HOPE provided an unprecedented collection of atmospheric dynamical, thermodynamical, and micro- and macrophysical properties of aerosols, clouds, and precipitation with high spatial and temporal resolution within a cube of approximately 10  ×  10  ×  10 km3. HOPE data will significantly contribute to our understanding of boundary layer dynamics and the formation of clouds and precipitation. The datasets have been made available through a dedicated data portal. First applications of HOPE data for model evaluation have shown a general agreement between observed and modelled boundary layer height, turbulence characteristics, and cloud coverage, but they also point to significant differences that deserve further investigations from both the observational and the modelling perspective

All-sky information content analysis for novel passive microwave instruments in the range from 23.8 to 874.4 GHz

We perform an all-sky information content analysis for channels in the millimetre and sub-millimetre wavelength with 24 channels in the region from 23.8 to 874.4 GHz. The employed set of channels corresponds to the instruments ISMAR and MARSS, which are available on the British FAAM research aircraft, and it is complemented by two precipitation channels at low frequencies from Deimos. The channels also cover ICI, which will be part of the MetOp-SG mission. We use simulated atmospheres from the ICON model as basis for the study and quantify the information content with the reduction of degrees of freedom (Delta DOF). The required Jacobians are calculated with the radiative transfer model ARTS. Specifically we focus on the dependence of the information content on the atmospheric composition. In general we find a high information content for the frozen hydrometeors, which mainly comes from the higher frequency channels beyond 183.31 GHz (on average 3.10 for cloud ice and 2.57 for snow). Considerable information about the microphysical properties, especially for cloud ice, can be gained. The information content about the liquid hydrometeors comes from the lower frequency channels. It is 1.69 for liquid cloud water and 1.08 for rain using the full set of channels. The Jacobians for a specific cloud hydrometeor strongly depend on the atmospheric composition. Especially for the liquid hydrometeors the Jacobians even change sign in some cases. However, the information content is robust across different atmospheric compositions. For liquid hydrometeors the information content decreases in the presence of any frozen hydrometeor, for the frozen hydrometeors it decreases slightly in the presence of the respective other frozen hydrometeor. Due to the lack of channels below 183 GHz liquid hydrometeors are hardly seen by ICI. However, the overall results with regard to the frozen hydrometeors also hold for the ICI sensor. This points to ICI\u27s great ability to observe ice clouds from space on a global scale with a good spatial coverage in unprecedented detail

The HD(CP)(2) Data Archive for Atmospheric Measurement Data

The archiving of scientific data is a sophisticated mission in nearly all research projects. In this paper, we introduce a new online archive of atmospheric measurement data from the High definition clouds and precipitation for advancing climate prediction (HD(CP)(2)) research initiative. The project data archive is quality managed, easy to use, and is now open for other atmospheric research data. The archive's creation was already taken into account during the HD(CP)(2) project planning phase and the necessary resources were granted. The funding enabled the HD(CP)(2) project to build a sound archive structure, which guarantees that the collected data are accessible for all researchers in the project and beyond