Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data
| Autor: | John Clyne, Allison H. Baker, Haiying Xu, Shaomeng Li, Dorit Hammerling |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
010504 meteorology & atmospheric sciences
Computer science 020207 software engineering Context (language use) Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology Lossy compression 01 natural sciences Computer engineering Compression (functional analysis) 0202 electrical engineering electronic engineering information engineering Multi method Climate simulation Simulation 0105 earth and related environmental sciences Data compression Data transmission |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319676296 ISC Workshops |
| Popis: | Earth System Model (ESM) simulations are increasingly constrained by the amount of data that they generate rather than by computational resources. The use of lossy data compression on model output can reduce storage costs and data transmission overheads, but care must be taken to ensure that science results are not impacted. Choosing appropriate compression algorithms and parameters is not trivial given the diversity of data produced by ESMs and requires an understanding of both the attributes of the data and the properties of the chosen compression methods. Here we discuss the properties of two distinct approaches for lossy compression in the context of a well-known ESM, demonstrating the different strengths of each, to motivate the development of an automated multi-method approach for compression of climate model output. |
| Databáze: | OpenAIRE |
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