Category Archives: HadCRUT4

Why scientific measurements need to be adjusted

There is an excellent piece in Ars Technica about why scientific measurements need to be adjusted, and the implications of this for climate data. It is written by Scott K Johnson and is called “Thorough, not thoroughly fabricated: The truth … Continue reading

Posted in American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, AMETSOC, Berkeley Earth Surface Temperature project, Canettes Blues Band, citizen data, climate data, data science, environment, evidence, geophysics, GISTEMP, HadCRUT4, mathematics education, meteorological models, obfuscating data, open data, physics, science, spatial statistics, Tamino, the right to know, the tragedy of our present civilization, Variable Variability | Leave a comment

Gavin Simpson updates his temperature analysis

See the very interesting discussion at his blog, From the bottom of the heap. It would be nice to see some information theoretic measures on these results, though.

Posted in AMETSOC, Anthropocene, astrophysics, Berkeley Earth Surface Temperature project, carbon dioxide, changepoint detection, climate, climate change, climate data, climate disruption, climate models, ecology, environment, evidence, Gavin Simpson, Generalize Additive Models, geophysics, global warming, HadCRUT4, hiatus, Hyper Anthropocene, information theoretic statistics, Kalman filter, maths, meteorology, numerical analysis, R, rationality, reasonableness, splines, time series | Leave a comment

New Paper Shows Global Climate Model Errors are Significantly Less Than Thought (Dan’s Wild Wild Science Journal)

New Paper Shows Global Climate Model Errors are Significantly Less Than Thought – Dan's Wild Wild Science Journal – AGU Blogosphere. The paper is here, unfortunately behind a paywall. I wonder if they looked at the temperature distributions’ second moments? … Continue reading

Posted in Arctic, carbon dioxide, climate, climate change, climate disruption, climate models, differential equations, diffusion processes, ensembles, environment, forecasting, geophysics, global warming, HadCRUT4, meteorology, model comparison, NASA, NCAR, NOAA, oceanography, open data, physics, prediction, rationality, reasonableness, science, statistics, Tamino, time series | Leave a comment