edu.ucar.opensky::articles:23769 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-25T06:39:56.598302 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d71c215n A statistical analysis of lossily compressed climate model data 2020-12-01T00:00:00Z publication https://n2t.org/ark:/85065/d71c215n https://doi.org/10.1016/j.cageo.2020.104599 Poppick, A. author Nardi, J. author Feldman, N. author Baker, Allison author Pinard, A. author Hammerling, D. M. author UCAR/NCAR - Library publisher The data storage burden resulting from large climate model simulations continues to grow. While lossy data compression methods can alleviate this burden, they introduce the possibility that key climate variables could be altered to the point of affecting scientific conclusions. Therefore, developing a detailed understanding of how compressed model output differs from the original is important. Here, we evaluate the effects of two leading compression algorithms, SZ and ZFP, on daily surface temperature and precipitation rate data from a widely used climate model. While both algorithms show promising fidelity with the original output, detectable artifacts are introduced even at relatively tight error tolerances. This study highlights the need for evaluation methods that are sensitive to errors at different spatiotemporal scales and specific to the particular climate variable of interest. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation