Earth System Model Evaluation Tool (ESMValTool) v2.0 – technical overview

Righi, Mattia; Andela, Bouwe; Eyring, Veronika; Lauer, Axel; Predoi, V.; Schlund, Manuel; Vegas-Regidor, Javier; Bock, Lisa; Brötz, Björn; Mora, L. De; Diblen, F.; Dreyer, Laura; Drost, Niels; Earnshaw, Paul; Haßler, Birgit; Koldunov, Nikolay; Little, Bill; Tomas, Saskia Loosveldt; Zimmermann, Klaus

doi:10.5194/gmd-13-1179-2020

Cited by 83 publications

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“…typically a netCDF file or a plot. This is explained in more detail in the companion paper Righi et al (2020), which we now explicitly refer to in the text in the revised paper.…”

Section: Line 57 -End-to-end Provenance -This Is Jargon What Does Thmentioning

confidence: 99%

“…Due to license issues, redistribution of observational data is not allowed in most cases, but the tool provides CMORizing scripts for each observational dataset used in the recipes that is not an obs4MIPs dataset. These scripts include detailed information on how to download and process the data for usage with the tool (see Righi et al (2020) for details).…”

Section: Line 972 -Are the Observations Available? Saying They Are Nomentioning

confidence: 99%

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Eyring¹

2020

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We thank the reviewer for the very detailed and helpful comments. We have now revised our manuscript in light of these and the other review comments we have received. A pointwise reply is given below. General comments: C1 GMDD Interactive commentPrinter-friendly version Discussion paperThis paper documents the latest version of the ESMValTool v2.0. The paper and the tool have lots of very good points. For example, one can reproduce IPCC Working Group 1 figures fairly easily. As an IPCC author and also a user of the IPCC, this alone makes the tool very valuable to our community. The ability to quickly assess the new CMIP6 models is equally valuable and so on. I strongly support the development of the tool.That said, I found the paper very hard to read and review. The authors want to discuss each option (what they call recipes) found in the tool. In describing the recipe, it is good to show a figure or 2 to help the reader appreciate what the tool can do. Given the large number of recipes, this makes the paper very long with many figures. There is a tension between showing the figures as examples and trying to make certain scientific points/conclusion with those figures. I understand this tension well as I have also tried to produce papers like this one.Scientists want to talk about the science, not just use the figure as an example. The problem is the caveats and sometimes the complete justification for the conclusion is left out because the science is not the point. It is an example.In this paper, there are conclusion sentences in the figure captions and figure caption text in the main body in many, many places. Cleaning these up would greatly help the readability of the paper. As a reader, I strongly dislike conclusions in the figure caption. This is especially true when the conclusion is not restated in the main text. The technique of giving conclusions in the caption is fine in a talk, but not in a paper. It just adds to the length. Also, many figure captions are missing units and other details needed to document the figure. Sometimes these details are found in the text, but they belong C2

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“…typically a netCDF file or a plot. This is explained in more detail in the companion paper Righi et al (2020), which we now explicitly refer to in the text in the revised paper.…”

Section: Line 57 -End-to-end Provenance -This Is Jargon What Does Thmentioning

confidence: 99%

Section: Line 972 -Are the Observations Available? Saying They Are Nomentioning

confidence: 99%

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Eyring¹

2020

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“…All recipes are included in the ESMValTool repository on GitHub. The directory structure of the ESMValTool is outlined in the technical description paper by Righi et al (2020). All recipes can be found in the directory https://github.com/ESMValGroup/ESMValTool/tree/master/esmvaltool/recipes.…”

Section: C7mentioning

confidence: 99%

“…For details, see Righi et al (2020). CF and CMOR references are now added in the revised manuscript and abbreviations are defined.…”

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Eyring¹

2020

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We thank the reviewer for the very detailed and helpful comments. We have now revised our manuscript in light of these and the other review comments we have received. A pointwise reply is given below. General comments: C1 GMDD Interactive commentPrinter-friendly version Discussion paperThis manuscript entails a monumental effort in attempting to facilitate the development and evaluation of climate models. Examples for analysis reproducibility, particularly output figures from IPCC chapters is commendable. A pathway to expand this to output figures in the literature is also evident. Model performance metrics, diagnostics for the evaluation of processes in different realms are presented in great detail along with the corresponding recipes. Example figures as a result of integrating community metrics is also shown in the manuscript. The flow and the content could be more consistent so the focus of ESMValTool goals and the impact in doing that is delivered as intended. Some level of brevity, citing references for details, providing more example figures from recipes, pointers to additional recipe documentation -should be made available through an external reference and/or supplementary material. Scalability and interoperability aspects can also be briefly touched upon, providing guidance to the community, making interoperability and practicalitya key to expanding the audience. There is scope for condensing and merging certain sections. Some key points to help improve readability is furnished below in specific comments. Overall, thank you for the contributions. Please see more comments below.Thanks for your suggestions. Please see our responses to the specific comments below how we have addressed them. Specific comments and technical corrections:Page1, Ln 58 Reproducibility -Specifics and explicit wording is required here, as to what aspect is targeted. C2 GMDD Interactive commentPrinter-friendly version Discussion paperWe have rephrased accordingly.Page2, Ln 85 There may be more references that need to be cited while discussing data standardization for CMIP. E.g. https://pcmdi.llnl.gov/mips/cmip5/CMIP5_output_metadata_requirements.pdf? More references added.Page 3, Ln 92-83: The line about "full rewards of the effort. . .." should be reworded to provide more of a positive tone to the available observations and model output in standardized format. Expanding what is meant by "full rewards" will be very helpful in this line, rather than the subsequent paragraph.

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Evaluation of a new 12 km regional perturbed parameter ensemble over Europe

et al. 2021

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We evaluate a 12-member perturbed parameter ensemble of regional climate simulations over Europe at 12 km resolution, carried out as part of the UK Climate Projections (UKCP) project. This ensemble is formed by varying uncertain parameters within the model physics, allowing uncertainty in future projections due to climate modelling uncertainty to be explored in a systematic way. We focus on present day performance both compared to observations, and consistency with the driving global ensemble. Daily and seasonal temperature and precipitation are evaluated as two variables commonly used in impacts assessments. For precipitation we find that downscaling, even whilst within the convection-parameterised regime, generally improves daily precipitation, but not everywhere. In summer, the underestimation of dry day frequency is worse in the regional ensemble than in the driving simulations. For temperature we find that the regional ensemble inherits a large wintertime cold bias from the global model, however downscaling reduces this bias. The largest bias reduction is in daily winter cold temperature extremes. In summer the regional ensemble is cooler and wetter than the driving global models, and we examine cloud and radiation diagnostics to understand the causes of the differences. We also use a low-resolution regional simulation to determine whether the differences are a consequence of resolution, or due to other configuration differences, with the predominant configuration difference being the treatment of aerosols. We find that use of the EasyAerosol scheme in the regional model, which aims to approximate the aerosol effects in the driving model, causes reduced temperatures by around 0.5 K over Eastern Europe in Summer, and warming of a similar magnitude over France and Germany in Winter, relative to the impact of interactive aerosol in the global runs. Precipitation is also increased in these regions. Overall, we find that the regional model is consistent with the global model, but with a typically better representation of daily extremes and consequently we have higher confidence in its projections of their future change.

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Earth System Model Evaluation Tool (ESMValTool) v2.0 – technical overview

Cited by 83 publications

References 50 publications

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Evaluation of a new 12 km regional perturbed parameter ensemble over Europe

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