Category Archives: Martyn Plummer

Less evidence for a global warming hiatus, and urging more use of Bayesian model averaging in climate science

(This post has been significantly updated midday 15th February 2018.) I’ve written about the supposed global warming hiatus of 2001-2014 before: “‘Overestimated global warming over the past 20 years’ (Fyfe, Gillett, Zwiers, 2013)”, 28 August 2013 “Warming Slowdown?”, Azimuth, Part … Continue reading

Posted in American Statistical Association, Andrew Parnell, anomaly detection, Anthropocene, Bayesian, Bayesian model averaging, Berkeley Earth Surface Temperature project, BEST, climate change, David Spiegelhalter, dependent data, Dublin, GISTEMP, global warming, Grant Foster, HadCRUT4, hiatus, Hyper Anthropocene, JAGS, Markov Chain Monte Carlo, Martyn Plummer, Mathematics and Climate Research Network, MCMC, model-free forecasting, Niamh Cahill, Significance, statistics, Stefan Rahmstorf, Tamino | 2 Comments

Rushing the +2 degree Celsius boundary

I made a comment on Google+ pertaining to a report of a recent NOAA finding. Enjoy. But remember that COP21 boundary is equivalent to 450 ppm CO2.

Posted in adaptation, AMETSOC, Anthropocene, atmosphere, Bill Nye, bridge to nowhere, carbon dioxide, Carbon Tax, Carbon Worshipers, citizenship, civilization, clean disruption, climate, climate disruption, COP21, corporate litigation on damage from fossil fuel emissions, differential equations, disruption, distributed generation, Donald Trump, ecology, El Nina, El Nino, energy, energy reduction, engineering, environment, environmental law, Epcot, explosive methane, forecasting, fossil fuel divestment, fossil fuels, geophysics, global warming, greenhouse gases, greenwashing, Hyper Anthropocene, investment in wind and solar energy, IPCC, local generation, Mark Jacobson, Martyn Plummer, microgrids, Miguel Altieri, philosophy, physical materialism, R, resiliency, Ricky Rood, risk, Sankey diagram | Leave a comment

“Grid shading by simulated annealing” [Martyn Plummer]

Source: Grid shading by simulated annealing (or what I did on my holidays), aka “fun with GCHQ job adverts”, by Martyn Plummer, developer of JAGS. Excerpt: I wanted to solve the puzzle but did not want to sit down with … Continue reading

Posted in approximate Bayesian computation, Bayesian, Bayesian inversion, Boltzmann, BUGS, Christian Robert, Gibbs Sampling, JAGS, likelihood-free, Markov Chain Monte Carlo, Martyn Plummer, mathematics, maths, MCMC, Monte Carlo Statistical Methods, optimization, probabilistic programming, SPSA, stochastic algorithms, stochastic search | Leave a comment