Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

Abstract The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB....

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Autores principales:	Zebedee Nicholls, Jared Lewis, Melissa Makin, Usha Nattala, Geordie Z. Zhang, Simon J. Mutch, Edoardo Tescari, Malte Meinshausen
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	aggregate climate CMIP model projections Meteorology. Climatology QC851-999 Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/1c0dbaeea795459c868e34d28d4db64b
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spelling	oai:doaj.org-article:1c0dbaeea795459c868e34d28d4db64b2021-11-23T13:44:37ZRegionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.02049-606010.1002/gdj3.113https://doaj.org/article/1c0dbaeea795459c868e34d28d4db64b2021-11-01T00:00:00Zhttps://doi.org/10.1002/gdj3.113https://doaj.org/toc/2049-6060Abstract The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text‐based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non‐specialists to access CMIP data in a new, user‐friendly way.Zebedee NichollsJared LewisMelissa MakinUsha NattalaGeordie Z. ZhangSimon J. MutchEdoardo TescariMalte MeinshausenWileyarticleaggregateclimateCMIPmodelprojectionsMeteorology. ClimatologyQC851-999GeologyQE1-996.5ENGeoscience Data Journal, Vol 8, Iss 2, Pp 154-198 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	aggregate climate CMIP model projections Meteorology. Climatology QC851-999 Geology QE1-996.5
spellingShingle	aggregate climate CMIP model projections Meteorology. Climatology QC851-999 Geology QE1-996.5 Zebedee Nicholls Jared Lewis Melissa Makin Usha Nattala Geordie Z. Zhang Simon J. Mutch Edoardo Tescari Malte Meinshausen Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0
description	Abstract The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text‐based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non‐specialists to access CMIP data in a new, user‐friendly way.
format	article
author	Zebedee Nicholls Jared Lewis Melissa Makin Usha Nattala Geordie Z. Zhang Simon J. Mutch Edoardo Tescari Malte Meinshausen
author_facet	Zebedee Nicholls Jared Lewis Melissa Makin Usha Nattala Geordie Z. Zhang Simon J. Mutch Edoardo Tescari Malte Meinshausen
author_sort	Zebedee Nicholls
title	Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0
title_short	Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0
title_full	Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0
title_fullStr	Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0
title_full_unstemmed	Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0
title_sort	regionally aggregated, stitched and de‐drifted cmip‐climate data, processed with netcdf‐scm v2.0.0
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/1c0dbaeea795459c868e34d28d4db64b
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Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

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