Category Archives: ensembles

A look at an electricity consumption series using SNCDs for clustering

(Slightly amended with code and data link, 12th January 2019.) Prediction of electrical load demand or, in other words, electrical energy consumption is important for the proper operation of electrical grids, at all scales. RTOs and ISOs forecast demand based … Continue reading

Posted in American Statistical Association, consumption, data streams, decentralized electric power generation, dendrogram, divergence measures, efficiency, electricity, electricity markets, energy efficiency, energy utilities, ensembles, evidence, forecasting, grid defection, hierarchical clustering, hydrology, ILSR, information theoretic statistics, local self reliance, Massachusetts, microgrids, NCD, normalized compression divergence, numerical software, open data, prediction, rate of return regulation, Sankey diagram, SNCD, statistical dependence, statistical series, statistics, sustainability, symmetric normalized compression divergence, time series | Leave a comment

“One of the most interesting things about the MIP ensembles is that the mean of all the models generally has higher skill than any individual model.” We hold these truths to be self-evident, that all models are created equal, that … Continue reading

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“Full-depth Ocean Heat Content” reblog

This is a re-blog of an excellent post at And Then There’s Physics, titled Full-depth OHC or, expanded, “full-depth ocean heat content”. Since my holiday is now over, I thought I might briefly comment on a recent paper by Cheng … Continue reading

Posted in Anthropocene, climate, climate change, climate data, climate disruption, climate models, computation, differential equations, ensembles, environment, fluid dynamics, forecasting, geophysics, global warming, greenhouse gases, Hyper Anthropocene, Lorenz, Mathematics and Climate Research Network, model comparison, NOAA, oceanography, physics, science, statistics, theoretical physics, thermodynamics, time series | Leave a comment

high dimension Metropolis-Hastings algorithms

If attempting to simulate from a multivariate standard normal distribution in a large dimension, when starting from the mode of the target, i.e., its mean γ, leaving the mode γis extremely unlikely, given the huge drop between the value of the density at the mode γ and at likely realisations Continue reading

Posted in Bayes, Bayesian, Bayesian inversion, boosting, chance, Christian Robert, computation, ensembles, Gibbs Sampling, James Spall, Jerome Friedman, Markov Chain Monte Carlo, mathematics, maths, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical software, numerics, optimization, reasonableness, Robert Schapire, SPSA, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, Yoav Freund | Leave a comment

“Causal feedbacks in climate change”

Today I was reviewing and re-reading the nonlinear time series technical literature I have, seeking ideas on how to go about using the statistical ensemble learning technique called “boosting” with them. (See the very nice book, R. E. Schapire, Y. … Continue reading

Posted in Anthropocene, boosting, Carbon Cycle, carbon dioxide, Carbon Worshipers, cat1, climate, climate change, climate data, climate disruption, complex systems, convergent cross-mapping, denial, differential equations, diffusion processes, dynamical systems, ecology, Egbert van Nes, empirical likelihood, ensembles, environment, Ethan Deyle, Floris Takens, forecasting, fossil fuels, geophysics, George Sughihara, global warming, greenhouse gases, Hao Ye, machine learning, Maren Scheffer, mathematics, maths, meteorology, physics, rationality, reasonableness, science, state-space models, Takens embedding theorem, time series, Timothy Lenton, Victor Brovkin | 2 Comments

November Hottest Ever, and Christmas Likely To bring Record Warmth in The East (Dan’s Wild Wild Science Journal; AGU Blogosphere)

The long-range guidance is showing strong indications that the incredible December warmth in the Eastern U.S. will continue to the end of the month. A blast of cold air will arrive later this week,… (Click on image for larger map, … Continue reading

Posted in AMETSOC, capricious gods, climate, climate models, Dan Satterfield, differential equations, diffusion processes, dynamical systems, ensembles, ENSO, environment, forecasting, geophysics, Hyper Anthropocene, meteorology, NCAR, NOAA, numerical software, physics, science, the right to know, wave equations | Leave a comment

Thoughts on “Regime Shift?”

John Baez at The Azimuth Project opened a discussion on the recent paper by Reid, et al Philip C. Reid et al, Global impacts of the 1980s regime shift on the Earth’s climate and systems, Global Change Biology, 2015. I … Continue reading

Posted in Bayesian, changepoint detection, climate change, climate disruption, climate models, dynamic linear models, ecology, ensembles, environment, global warming, population biology, Rauch-Tung-Striebel, regime shifts, state-space models, stochastic algorithms, time series | Leave a comment

Southern New England Meteorology Conference, 24th October 2015

I attending the 2015 edition of the Southern New England Meteorology Conference in Milton, MA, near the Blue Hill, and its Blue Hill Climatological Observatory, of which I am a member as we as of the American Meteorological Society. I … Continue reading

Posted in Anthropocene, capricious gods, climate, Dan Satterfield, dynamical systems, ensembles, ENSO, environment, floods, forecasting, geophysics, Hyper Anthropocene, information theoretic statistics, mesh models, meteorology, model comparison, NCAR, NOAA, nor'easters, oceanography, probability, science, spatial statistics, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, time series | 1 Comment

Questions About El Nino Answered – Dan’s Wild Wild Science Journal – AGU Blogosphere

Source: Questions About El Nino Answered – Dan’s Wild Wild Science Journal – AGU Blogosphere

Posted in bifurcations, capricious gods, chance, climate change, Dan Satterfield, ensembles, ENSO, games of chance, maths, meteorology, NOAA, nor'easters, oceanography, precipitation, prediction, rationality, reasonableness, risk, science, spatial statistics | Leave a comment

Your future: Antarctica, in detail

Climate and geophysical accuracy demands fine modeling grids, and very large supercomputers. The best and biggest supercomputers have not been available for climate work, until recently. Watch how results differ if fine meshes and big supercomputers are used. Why haven’t … Continue reading

Posted in Antarctica, Anthropocene, bridge to nowhere, climate, climate change, climate disruption, climate zombies, disingenuity, ecology, ensembles, forecasting, geophysics, global warming, Hyper Anthropocene, ignorance, IPCC, Lawrence Berkeley National Laboratory, LBNL, living shorelines, mathematics, mathematics education, maths, mesh models, meteorology, multivariate statistics, numerical software, optimization, physics, rationality, reasonableness, risk, science, science education, sea level rise, spatial statistics, state-space models, statistics, stochastic algorithms, stochastics, supercomputers, temporal myopia, the right to know, thermodynamics, time series, University of California Berkeley, WAIS | Leave a comment

“The Bayesian Second Law of Thermodynamics” (Sean Carroll, and collaborators)

http://www.preposterousuniverse.com/blog/2015/08/11/the-bayesian-second-law-of-thermodynamics/ See also.

Posted in approximate Bayesian computation, Bayesian, bifurcations, Boltzmann, capricious gods, dynamical systems, ensembles, games of chance, Gibbs Sampling, information theoretic statistics, Josiah Willard Gibbs, mathematics, maths, physics, probability, rationality, reasonableness, science, statistics, stochastic algorithms, stochastics, thermodynamics, Wordpress | 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

Thank You

Originally posted on Open Mind:
To all the readers who make this blog worth writing: Thank you. Thank you for sharing my work. One of the things that makes me proud is that often my blog posts are used as…

Posted in astrophysics, citizen science, climate change, climate data, climate disruption, climate education, climate models, differential equations, dynamical systems, ecology, ensembles, forecasting, games of chance, geophysics, global warming, hiatus, Hyper Anthropocene, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, new forms of scientific peer review, open data, open source scientific software, physics, probabilistic programming, probability, rationality, reasonableness, reproducible research, risk, science, science education, spatial statistics, statistics, Tamino, the right to know, time series, transparency | Leave a comment

“Why Using El Nino to Forecast the Winter is Risky” – Dan’s Wild Wild Science Journal

Why Using El Nino to Forecast the Winter is Risky – Dan's Wild Wild Science Journal – AGU Blogosphere.

Posted in chance, climate models, differential equations, dynamical systems, ensembles, ENSO, environment, forecasting, geophysics, history, mathematics, meteorology, NCAR, NOAA, nor'easters, oceanography, physics, risk, science, statistics | Leave a comment

‘Weather by Icon’ Is A Bad Way To Get an Accurate Forecast – Dan’s Wild Wild Science Journal – AGU Blogosphere

'Weather by Icon' Is A Bad Way To Get an Accurate Forecast – Dan's Wild Wild Science Journal – AGU Blogosphere.

Posted in dynamical systems, ensembles, environment, forecasting, geophysics, history, hurricanes, maths, meteorology, NCAR, NOAA, nor'easters, physics, probability, rationality, science, science education, statistics, temporal myopia | Leave a comment

Destroying the Most Persistent Scientific Myth In America – Dan’s Wild Wild Science Journal – AGU Blogosphere

Destroying the Most Persistent Scientific Myth In America – Dan's Wild Wild Science Journal – AGU Blogosphere.

Posted in Bayesian, biology, carbon dioxide, chance, citizen science, climate, climate change, climate disruption, climate education, denial, ecology, education, ensembles, environment, forecasting, geophysics, global warming, hiatus, history, IPCC, meteorology, NCAR, NOAA, obfuscating data, physics, probability, rationality, reasonableness, science, science education, spatial statistics, statistics, temporal myopia, time series | Leave a comment

“NOAA temperature record updates and the ‘hiatus’” (from Gavin at REALCLIMATE)

NOAA temperature record updates and the ‘hiatus’. No doubt there’ll be, as Dr Schmidt says, a howl of protests that the data are “being manipulated”. There’s more discussion by Professor Mann. But, more to the point, it looks like we’re … Continue reading

Posted in chance, citizen science, climate, climate change, climate disruption, climate education, climate models, diffusion processes, dynamical systems, energy, ensembles, forecasting, geophysics, global warming, hiatus, maths, meteorology, model comparison, NASA, NCAR, NOAA, oceanography, physics, rationality, spatial statistics, statistics, stochastics, temporal myopia, time series | 2 Comments

“Storm-proven forecasting gets yearlong trial”

Storm-studying scientists have made their next-generation forecasting system available online so the wider weather community can put it to the test. After using the real-time system during short-lived field research campaigns, developers at the National Center for Atmospheric Research (NCAR) … Continue reading

Posted in citizen science, ensembles, ENSO, environment, forecasting, geophysics, maths, meteorology, NCAR, open data, physics, precipitation, science, science education, scientific publishing, spatial statistics, statistics | Leave a comment