Niklas Röber

Visualization of 2D Uncertainty in Decadal Climate Predictions

In recent years, climate prediction systems based on coupled climate models are used for investigating the climate predictability on a decadal time scale. Based on ensemble simulation techniques applied and hindcast experiments carried out first, the predictive skill of a system can be derived. The ensemble simulations used for the decadal climate predictions enable the issuing of probabilistic information along with the quantities predicted. In this work, we focus on the concurrent visualization of three related 2D fields: the forecast variable, here the 2m temperature anomaly, along with the corresponding predictive skill and the ensemble spread. We show exemplary solutions produced with three different visualization systems: NCL, Avizo Green and ParaView.

Visualization in meteorology --- A survey of techniques and tools for data analysis tasks

This article surveys the history and current state of the art of visualization in meteorology, focusing on visualization techniques and tools used for meteorological data analysis. We examine characteristics of meteorological data and analysis tasks, describe the development of computer graphics methods for visualization in meteorology from the 1960s to today, and visit the state of the art of visualization techniques and tools in operational weather forecasting and atmospheric research. We approach the topic from both the visualization and the meteorological side, showing visualization techniques commonly used in meteorological practice, and surveying recent studies in visualization research aimed at meteorological applications. Our overview covers visualization techniques from the fields of display design, 3D visualization, flow dynamics, feature-based visualization, comparative visualization and data fusion, uncertainty and ensemble visualization, interactive visual analysis, efficient rendering, and scalability and reproducibility. We discuss demands and challenges for visualization research targeting meteorological data analysis, highlighting aspects in demonstration of benefit, interactive visual analysis, seamless visualization, ensemble visualization, 3D visualization, and technical issues.

Icosahedral maps for a multiresolution representation of earth data

The icosahedral non-hydrostatic (ICON) model is a digital Earth model based on an icosahedral representation and used for numerical weather prediction. In this paper, we introduce icosahedral maps that are designed to fit the geometry of different cell configurations in the ICON model. These maps represent the connectivity information in ICON in a highly structured two-dimensional hexagonal representation that can be adapted to fit different cell configurations. Our maps facilitate the execution of a multiresolution analysis on the ICON model. We demonstrate this by applying a hexagonal version of the discrete wavelet transform in conjunction with our icosahedral maps to decompose ICON data to different levels of detail and to compress it via a thresholding of the wavelet coefficients.