Due to the current gap in continued funding from the U.S. National Science Foundation (NSF), the NSF Unidata Program Center has temporarily paused most operations. See NSF Unidata Pause in Most Operations for details.
Howdy NetCDF Users! Compression is one of the most popular and useful features of netCDF/HDF5 files, and compress also plays an important role in the new Zarr format. Yet the zlib library is showing it's age - it's slow! There is a new, faster, drop-in replacement, zlib-ng. Give it a try to speed up your processing with no code changes: https://github.com/zlib-ng/zlib-ng. Zlib provides lossless compression, but lossy compression can be much more effective, at the cost of some changes to the data. With the new nc_def_var_quantize()/nc_inq_var_quantize() functions (which will be in the next netCDF release), you can now specify a number of significant digits for a variable. Then, turn on compression to get lossy compression, but to preserve that number of significant digits. More on zlib-ng, quantization, and other compression topics can be found in this extended abstract presented at the AGU this week. Co-authos include Charlie Zender (of bitgroom fame), Ward Fisher and Dennis Heimbigner (Unidata netCDF programmers), and Hang Lei, Brian Curtis, and Kyle Gerheiser of NOAA EMC, where we have great interest in compressing our data. ;-) Get the extended abstract here: https://www.researchgate.net/publication/357001251_Quantization_and_Next-Generation_Zlib_Compression_for_Fully_Backward-Compatible_Faster_and_More_Effective_Data_Compression_in_NetCDF_Files Get a slideshow of the results here: https://www.researchgate.net/publication/357000984_Quantization_and_Next-Generation_Zlib_Compression_for_Fully_Backward-Compatible_Faster_and_More_Effective_Data_Compression_in_NetCDF_Files Keep on NetCDFing! Ed Hartnett
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