A recent publication by the Scientific Computing Center (SCC), produced in cooperation with the Institute for Meteorology and Climate Research - Atmospheric Trace Gases and Remote Sensing (IMK-ASF), was given the Best Paper Award at the 13th IEEE eScience Conference.
The main advantage of the method proposed in the paper is that the quality of lossy compression of measured climatic time series data can be increased without significantly increasing the size of the compressed file. This method is to be used in an advanced form in the development of a compression algorithm for climate data. This algorithm aims to reduce the large data volumes of several hundred terabytes by a substantial amount.
In accordance with the position of principle adopted in March 2010 and the subsequent support of the Open Access Conventions, all resources such as data, program code and presentation material are public and freely available.
| Title | Adaptive Lossy Compression of Complex Environmental Indices using Seasonal Auto Regressive Integrated Moving Average Models |
| Bibliography | https://publikationen.bibliothek.kit.edu/1000076761 |
| Resources | https://github.com/ucyo/adaptive-lossy-compression |
| Contact | Uğur Çayoğlu |