Sixty Years of Widespread Warming in the Southern Middle and High Latitudes (1957–2016)

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review

Jones, M. E., Bromwich, D. H., Nicolas, J. P., Carrasco, J., Plavcová, E., Zou, X., & Wang, S. (2019). Sixty Years of Widespread Warming in the Southern Middle and High Latitudes (1957–2016), Journal of Climate, 32(20), 6875-6898. https://doi.org/10.1175/JCLI-D-18-0565.1

Occasionally, I get asked what is going on with the Antarctic. While the Arctic is warming faster than the global average¹, the Antarctic seems to be doing its own thing (be it sea ice, temperature, ocean heat, penguins³) and it’s always slightly counterintuitive. This paper looks at one of the major influences on temperature in the Antarctic and the mid-to-high latitudes of the Southern Hemisphere, the Southern Annular Mode. It suggests that if one somehow removes the effects of the Southern Annular Mode then warming is more uniform across the hemisphere, which would be neat as it explains quite a lot.

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Internal variability plays a dominant role in global climate projections of temperature and precipitation extremes

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review, uncertainty

Blanusa, M.L., López-Zurita, C.J. & Rasp, S. Internal variability plays a dominant role in global climate projections of temperature and precipitation extremes. Clim Dyn (2023). https://doi.org/10.1007/s00382-023-06664-3

It’s a paper on the relative uncertainties in predictions (not projections as the title suggests as it treats scenarios as an uncertainty) of extreme events arising from: internal variability, model uncertainty and scenario uncertainty. The extreme events are once in a decade daily precip or Tmax values and they are asking about the predictability of the exact number of events over a particular time window. Unsurprisingly, internal variability is a large component of this mix in the near future. For precip it remains a large component in many regions out to the end of the century. The intro says “If internal variability makes up a large fraction of the total variability, even a significant model improvement would only lead to a minor reduction in total uncertainty”. As internal variability constitutes a large fraction of the variability, they conclude that there is less to be gained from reducing model uncertainty and that ensembles are important. I agree with the latter claim.

I have one major overarching criticism, but upfront I’ll say this is a well written paper, clearly expressed and illustrated and it looks like a good deal of thought went into assessing sensitivity to various choices made, at least within the boundaries set by the original question.

Quantifying Daytime Heating Biases in Marine Air Temperature Observations from Ships

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review, uncertainty

Cropper, T. E., Berry, D. I., Cornes, R. C., & Kent, E. C. (2023). Quantifying Daytime Heating Biases in Marine Air Temperature Observations from Ships, Journal of Atmospheric and Oceanic Technology https://doi.org/10.1175/JTECH-D-22-0080.1

Another Year of…

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review

Cheng et al. have published their annual “Another year of record heat for the oceans” paper. I love the weariness of the title. Again. It happened, again, and it will go on happening again and again until greenhouse gas concentrations stop rising. Anyway…

One in a series of (very very) occasional paper reviews.

Was that 1.5°C? Was it wearing a hat and waving?

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review

Assessing Internal Variability of Global Mean Surface Temperature from Observational Data and Implications for Reaching Key Thresholds is the wordy title of a paper which aims to answer the question, how will we know when global temperature has passed 1.5°C above pre-industrial? It’s paywalled, but googling the title gave me an accessible pdf of the manuscript.

The alleged global warming hiatus

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review

Theodore G. Shepherd has a new paper “Bringing physical reasoning into statistical practice in climate-change science” which looks at the disconnect between physical reasoning and statistical practice and bringing the former into the latter. It rails against Null Hypothesis Significance Testing. There’s a grand tradition of papers doing this and they are invariably interesting to read even though the message is usually a variation on a well known theme. This paper talks more generally about statistical rituals of which NHST is but one and Shepherd notes that he’s occasionally to be seen performing a ritual or two himself (who isn’t?):

I suspect I am not alone in admitting that most of the statistical tests in my own papers are performed in order to satisfy these rituals, rather than as part of the scientific discovery process itself.

It outlines instances where rituals can get you into trouble (multiple testing, base rate neglect, prosecutor fallacy etc.) and this is all fair enough and all familiar ground. The interesting variations involve delving into the assumptions of NHST. Science can be complex, particularly climate science, so care should be taken not to over simplify. At the same time, complexity isn’t necessarily to be favoured.

It’s all very complex.

Or simple.

The earth is a sphere

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review

Peters Guttorp and Craigmile have written an interesting technote – “A combined estimate of global temperature” which appeared recently in my Google Scholar feed. The note is interesting and potentially very useful. [spoiler: I don’t think it realises that potential, but I think it’s still interesting].

Urban heat islands can explain anything

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review

Scafetta 2021 was published in Climate Dynamics and it’s the kind of publishing decision that makes you rethink the reputation of a journal. The author thanks three reviewers for their useful comments but the paper reads as if those comments were not heeded. A quick read through is enough to identify several obvious weaknesses that should have been addressed before publication*.

An initial look at Kadow et al.

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review

A paper published in Nature Geoscience yesterday uses a neural network* to fill gaps in the HadCRUT4 global temperature data set. I’m always excited to see new approaches to reconstructing historical data and this paper uses a technique that is very different from those employed by other teams that have had a go at the problem. That alone, I think, makes it valuable – it is important to explore structurally-different approaches to the problem, the better to explore structural uncertainty. Anyway, go and read it. It’s short nicely written and very accessible. Then come back here and laugh at my terrible description.

The impossibility of lunchtime theft in the mind of the amateur statistician

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review

I’ve read the Risbey paper a few times now and, from first reading to last, it struck me as a very odd bird*. On the one claw it is billed as a topical review (which I think means you have to rub it onto areas of dried skin), but it’s not really a review. It has a list of papers tucked under its wing, which it treats as “data”, burying them in an Appendix rather than citing themª. There’s very little actual reviewing in the common sense. On the other claw, it presents a novel statistical analysis, which they claim shows, at best, very weak evidence for the statistical specialness of a period against whose popular name the authors have pitched their combined statistical and rhetorical powers.