machine-learning
-
Probably a terrible idea
More bad ideas for sticking datasets together like wiggly worms. Continue reading
-
For skies of couple-colour as a brinded cow
Some time ago, I posted on a global temperature dataset by Kadow et al. – Artificial intelligence reconstructs missing climate information – which was created using neural nets to infill data gaps. It was used in the last IPCC report alongside the more traditional datasets: HadCRUT5, Berkeley Earth, and NOAAGlobalTemp. The other three datasets are… Continue reading
-
People are afraid to merge
With the publication of Sippel et al. I’m back to considering structural uncertainty in global mean temperatures. I came up with a scheme for merging global temperature series that’s intended to balance estimates according to how closely related their methods are. Datasets that are variations on a single theme – such as the group of… Continue reading
-
It just ain’t natural
A new paper on SST biases is in NatureorScience. It’s titled “Early-twentieth-century cold bias in ocean surface temperature observations“. It’s a little strange, given the prominence of natureorncience that the main result – that there is a cold bias in the early 20th century global temperatures originating in the ocean data – has been published… Continue reading
Diagram Monkey 