A modular software framework for compression of structured climate data-Reference-Cited by-同舟云学术

A modular software framework for compression of structured climate data

Published:2018-11-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Author:

Cayoglu Ugur,Schröter Jennifer,Meyer Jörg,Streit Achim¹,Braesicke Peter¹

Affiliation:

1. Karlsruhe Institute of Technology, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3274895.3274897

Reference14 articles.

1. Allison H. Baker Dorit M. Hammerling Sheri A. Mickleson Haiying Xu Martin B. Stolpe Phillipe Naveau Ben Sanderson Imme Ebert-Uphoff Savini Samarasinghe Francesco De Simone Francesco Carbone Christian N. Gencarelli John M. Dennis Jennifer E. Kay and Peter Lindstrom. 2016. Evaluating Lossy Data Compression on Climate Simulation Data within a Large Ensemble. Geosci. Model Dev. Discuss. July (jul 2016) 1--38. Allison H. Baker Dorit M. Hammerling Sheri A. Mickleson Haiying Xu Martin B. Stolpe Phillipe Naveau Ben Sanderson Imme Ebert-Uphoff Savini Samarasinghe Francesco De Simone Francesco Carbone Christian N. Gencarelli John M. Dennis Jennifer E. Kay and Peter Lindstrom. 2016. Evaluating Lossy Data Compression on Climate Simulation Data within a Large Ensemble. Geosci. Model Dev. Discuss. July (jul 2016) 1--38.

2. Ugur Cayoglu. 2018. Prediction-based Compression Framework. https://github.com/ucyo/cframework. (2018). {Online; accessed 27-May-2018}. Ugur Cayoglu. 2018. Prediction-based Compression Framework. https://github.com/ucyo/cframework. (2018). {Online; accessed 27-May-2018}.

3. Ugur Cayoglu Peter Braesicke Tobias Kerzenmacher Jörg Meyer and Achim Streit. 2017. Adaptive Lossy Compression of Complex Environmental Indices Using Seasonal Auto-Regressive Integrated Moving Average Models. In 2017 IEEE 13th International Conference on e-Science (e-Science). 315--324. Ugur Cayoglu Peter Braesicke Tobias Kerzenmacher Jörg Meyer and Achim Streit. 2017. Adaptive Lossy Compression of Complex Environmental Indices Using Seasonal Auto-Regressive Integrated Moving Average Models. In 2017 IEEE 13th International Conference on e-Science (e-Science) . 315--324.

4. xarray: N-D labeled Arrays and Datasets in Python

5. Czip: A Fast Lossless Compression Algorithm for Climate Data