Abstract 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.

中文翻译：

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有损压缩气候模型数据的统计分析

摘要 大型气候模型模拟导致的数据存储负担持续增加。虽然有损数据压缩方法可以减轻这种负担，但它们引入了关键气候变量可能被改变到影响科学结论的程度的可能性。因此，详细了解压缩模型输出与原始输出有何不同非常重要。在这里，我们评估了两种领先的压缩算法 sz 和 zfp 对来自广泛使用的气候模型的每日地表温度和降水率数据的影响。虽然这两种算法都显示出对原始输出的有希望的保真度，但即使在相对严格的容错范围内也会引入可检测的伪影。