The 7590 most puissant researchers of the year

Our biannual list recognises the most influential researchers, the true pioneers of science, the giants on whose shoulders the rest of us stand like so many flakes of dandruff, the ones who made the most impact, the ones that were on the telly all the time, who had a scienceornature paper (or two or three) and got interviewed about that thing with the hyperventilating press release, who got the most citations, or caused a stir, the movers and shakers who moved things and er… shook, because we felt like they didn’t have enough attention already.

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The library where I grew up

The library where I grew up was like a building from the future, with exciting organic shapes cast in concrete and a brightly coloured spiral staircase. Every wall was covered in shelves so sunlight crept in at ceiling level through a narrow strip of window. On summer afternoons, the sun came through at an angle like laser beams that made the dust motes boil in the still air.

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Was 2020 the warmest year on record?

In which I continue an occasional series (2014, 2015) on whether particular years are the warmest on record.

A question I have been asked many time since about March 2020 was whether 2020 was going to be the warmest year on record and then, once the new year was rung in, whether 2020 was the warmest year on record? In a sense, the answer – the correct answer I would aver – hasn’t changed since March: it was maybe then, and it is maybe now. Some years are too close to call and 2020 was one such.

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Urban heat islands can explain anything

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*.

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An initial look at Kadow et al.

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. Continue reading

National Climate Monitoring Products

A National Climate Monitoring Product is something like the “mean temperature anomaly for the UK” or “Highest daily rainfall total in Spain in 2019”. It’s a summary of the weather and climate for a particular country.

The WMO Expert Team on National Climate Monitoring Products has written guidance to define a set of six basic National Climate Monitoring Products (let’s call them NCMPs from now on) which are:

  1.  Mean temperature anomaly averaged across the country
  2.  Total rainfall anomaly averaged across the country
  3.  Standardised precipitation index averaged across the country
  4.  Warm days averaged across the country
  5. Cold nights averaged across the country
  6.  Counts of station records (the odd one out)

The idea is that all Met Services that measure temperature and rainfall – which, by survey, we know is most of them – can calculate these products and use them to understand how weather and climate are changing in their country. Some countries produce some or all of these already and the idea’s not to replace what’s already being done, but to give countries with fewer resources a core set of products to aim for.

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