This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
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Abstract
Data from some climate model simulations is in a 360 days per year format, that is, every month is 30 days long. The main reason for this is analytical convenience in creating seasonal, annual and multi-annual means which are an integral part of climate model development and evaluation. This work illustrates a method to convert daily-mean, 360-day calendar climate model data into 'real', Gregorian calendar format. The method includes randomisation of the interpolation dates to avoid spurious artefacts in the output data, support for leap years and the ability to be run in in parallel so that multiple variables and years can be processed simultaneously. Future work to generalise this software to allow for sub-daily output frequency is encouraged and it is hoped that this work facilitates easier inter-model comparisons and knowledge transfer.
DOI
https://doi.org/10.31223/X5M081
Subjects
Climate, Earth Sciences, Meteorology, Physical Sciences and Mathematics
Keywords
climate, climate modelling, python, Gregorian, 360-day calendar, Jupyter
Dates
Published: 2023-07-05 23:42
Last Updated: 2023-07-06 06:42
License
CC BY Attribution 4.0 International
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Data Availability (Reason not available):
Publicly accessible and open source.
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