### Distributed Solar: The Democratizaton of Energy

### Blogroll

- What If
- The Keeling Curve: its history
- distributed solar and matching location to need
- Darren Wilkinson's introduction to ABC
- American Association for the Advancement of Science (AAAS)
- Higgs from AIR describing NAO and EA
- Team Andrew Weinberg
- Harvard's Project Implicit
- The Mermaid's Tale
- Survey Methodology, Prof Ron Fricker

### climate change

- Model state level energy policy for New Englad
- The beach boondoggle
- "Impacts of Green New Deal energy plans on grid stability, costs, jobs, health, and climate in 143 countries" (Jacobson, Delucchi, Cameron, et al)
- NOAA Annual Greenhouse Gas Index report
- SolarLove
- Transitioning to fully renewable energy
- "Betting strategies on fluctuations in the transient response of greenhouse warming"
- Nick Bower's "Scared Scientists"
- Berkeley Earth Surface Temperature
- Équiterre

### Archives

### Jan Galkowski

# Category Archives: numerical analysis

## JIGSAW-GEO v1.0

See: D. Engwirda, 2017: JIGSAW-GEO (1.0): Locally orthogonal staggered unstructured grid generation for general circulation modelling on the sphere, Geosci. Model Dev., 10, 2117-2140, doi:10.5194/gmd-10-2117-2017 and a general description at NASA. The figure below is copied from there.

## Sampling: Rejection, Reservoir, and Slice

An article by Suilou Huang for catatrophe modeler AIR-WorldWide of Boston about rejection sampling in CAT modeling got me thinking about pulling together some notes about sampling algorithms of various kinds. There are, of course, books written about this subject, … Continue reading

Posted in accept-reject methods, American Statistical Association, Bayesian computational methods, catastrophe modeling, data science, diffusion processes, empirical likelihood, Gibbs Sampling, insurance, Markov Chain Monte Carlo, mathematics, Mathematics and Climate Research Network, maths, Monte Carlo Statistical Methods, multivariate statistics, numerical algorithms, numerical analysis, numerical software, numerics, percolation theory, Python 3 programming language, R statistical programming language, Radford Neal, sampling, slice sampling, spatial statistics, statistics, stochastic algorithms, stochastic search
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## When linear systems can’t be solved by linear means

Linear systems of equations and their solution form the cornerstone of much Engineering and Science. Linear algebra is a paragon of Mathematics in the sense that its theory is what mathematicians try to emulate when they develop theory for many … Continue reading

## on nonlinear dynamics of hordes of people

I spent a bit of last week at a symposium honoring the work of Charney and Lorenz in fluid dynamics. I am no serious student of fluid dynamics. I have a friend, Klaus, an engineer, who is, and makes a … Continue reading

Posted in Anthropocene, bifurcations, biology, Carl Safina, causation, complex systems, dynamic generalized linear models, dynamic linear models, dynamical systems, ecological services, ecology, Emily Shuckburgh, finance, Floris Takens, fluid dynamics, fluid eddies, games of chance, Hyper Anthropocene, investments, Lenny Smith, Lorenz, nonlinear, numerical algorithms, numerical analysis, politics, population biology, population dynamics, prediction markets, Principles of Planetary Climate, public transport, Ray Pierrehumbert, risk, sampling networks, sustainability, Timothy Lenton, Yale University Statistics Department, zero carbon, ``The tide is risin'/And so are we''
1 Comment

## A new feature: Technical publications of the week

I’m beginning a new style of column, called technical publications of the week. While I can’t promise these will be weekly, I will, from time to time, highlight technical publications I’ve recently read which I consider to be noteworthy. I … Continue reading

Posted in Anthropocene, big data, climate change, climate disruption, data science, data streams, earthquakes, geophysics, global warming, Hyper Anthropocene, Locality Sensitive Hashing, LSH, MinHash, numerical algorithms, numerical analysis, random projections, seismology, subspace projection methods, SVD, the right to be and act stupid, the tragedy of our present civilization, the value of financial assets
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## Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION: A Review

(Revised and updated Monday, 24th October 2016.) Weapons of Math Destruction, Cathy O’Neil, published by Crown Random House, 2016. This is a thoughtful and very approachable introduction and review to the societal and personal consequences of data mining, data science, … Continue reading

Posted in citizen data, citizen science, citizenship, civilization, compassion, complex systems, criminal justice, Daniel Kahneman, data science, deep recurrent neural networks, destructive economic development, economics, education, engineering, ethics, Google, ignorance, Joseph Schumpeter, life purpose, machine learning, Mathbabe, mathematics, mathematics education, maths, model comparison, model-free forecasting, numerical analysis, numerical software, open data, optimization, organizational failures, planning, politics, prediction, prediction markets, privacy, rationality, reason, reasonableness, risk, silly tech devices, smart data, sociology, Techno Utopias, testing, the value of financial assets, transparency
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## Repaired R code for Markov spatial simulation of hurricane tracks from historical trajectories

(Slight update, 28th June 2020.) I’m currently studying random walk and diffusion processes and their connections with random fields. I’m interested in this because at the core of dynamic linear models, Kalman filters, and state-space methods there is a random … Continue reading

Posted in American Meteorological Association, American Statistical Association, AMETSOC, Arthur Charpentier, atmosphere, diffusion, diffusion processes, dynamic linear models, dynamical systems, environment, geophysics, hurricanes, Kalman filter, Kerry Emanuel, Lévy flights, Lorenz, Markov chain random fields, mathematics, mathematics education, maths, MCMC, mesh models, meteorological models, meteorology, model-free forecasting, Monte Carlo Statistical Methods, numerical analysis, numerical software, oceanography, open data, open source scientific software, physics, random walk processes, random walks, science, spatial statistics, state-space models, statistical dependence, statistics, stochastic algorithms, stochastics, time series
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## Bayesian blocks via PELT in R

The Bayesian blocks algorithm of Scargle, Jackson, Norris, and Chiang has an enthusiastic user community in astrostatistics, in data mining, and among some in machine learning. It is a dynamic programming algorithm (see VanderPlas referenced below) and, so, exhibits optimality … Continue reading

Posted in American Statistical Association, AMETSOC, anomaly detection, astrophysics, Cauchy distribution, changepoint detection, engineering, geophysics, multivariate statistics, numerical analysis, numerical software, numerics, oceanography, population biology, population dynamics, Python 3, quantitative biology, quantitative ecology, R, Scargle, spatial statistics, square wave approximation, statistics, stepwise approximation, time series, Woods Hole Oceanographic Institution
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## data.table

R provides a helpful data structure called the “data frame” that gives the user an intuitive way to organize, view, and access data. Many of the functions that you would us… Source: Intro to The data.table Package

## On Smart Data

One of the things I find surprising, if not astonishing, is that in the rush to embrace Big Data, a lot of learning and statistical technique has been left apparently discarded along the way. I’m hardly the first to point … Continue reading

Posted in Akaike Information Criterion, Bayes, Bayesian, Bayesian inversion, big data, bigmemory package for R, changepoint detection, data science, data streams, dlm package, dynamic generalized linear models, dynamic linear models, dynamical systems, Generalize Additive Models, generalized linear models, information theoretic statistics, Kalman filter, linear algebra, logistic regression, machine learning, Markov Chain Monte Carlo, mathematics, mathematics education, maths, maximum likelihood, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical analysis, numerical software, numerics, quantitative biology, quantitative ecology, rationality, reasonableness, sampling, smart data, state-space models, statistical dependence, statistics, the right to know, time series
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## 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
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## Of my favorite things …

(Clarifying language added 4 Apr 2016, 12:26 EDT.) I just watched an episode from the last season of Star Trek: The Next Generation entitled “Force of Nature.” As anyone who pays the least attention to this blog knows, opposing human … Continue reading

Posted in Anthropocene, bridge to somewhere, bucket list, Buckminster Fuller, Carl Sagan, climate, climate change, climate disruption, climate education, compassion, data science, Earle Wilson, ecology, Ecology Action, environment, evolution, geophysics, George Sughihara, global warming, Hyper Anthropocene, life purpose, mathematics, mathematics education, maths, numerical analysis, optimization, philosophy, physical materialism, physics, population biology, population dynamics, proud dad, quantitative biology, quantitative ecology, rationality, reasonableness, science, sociology, statistics, stochastic algorithms
5 Comments

## Phytoplankton-delineated oceanic eddies near Antarctica

Excerpt, from NASA: Phytoplankton are the grass of the sea. They are floating, drifting, plant-like organisms that harness the energy of the Sun, mix it with carbon dioxide that they take from the atmosphere, and turn it into carbohydrates and … Continue reading

Posted in AMETSOC, Antarctica, Arctic, bacteria, Carbon Cycle, complex systems, differential equations, diffusion, diffusion processes, dynamic linear models, dynamical systems, Emily Shuckburgh, environment, fluid dynamics, geophysics, GLMs, John Marshall, marine biology, Mathematics and Climate Research Network, NASA, numerical analysis, numerical software, oceanic eddies, oceanography, physics, phytoplankton, science, thermohaline circulation, WHOI, Woods Hole Oceanographic Institution
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## Generating supports for classification rules in black box regression models

Inspired by the extensive and excellent work in approximate Bayesian computation (see also), especially that done by Professors Christian Robert and colleagues (see also), and Professor Simon Wood (see also), it occurred to me that the complaints regarding lack of … Continue reading

Posted in approximate Bayesian computation, Bayes, Bayesian, Bayesian inversion, generalized linear models, machine learning, numerical analysis, numerical software, probabilistic programming, rationality, reasonableness, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, support of black boxes
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## El Nino In A Can – Dan’s Wild Wild Science Journal – AGU Blogosphere

Click the image above to see a video from the GFDL CM2.6 climate model. This is NOT this year’s El Nino. When you start a climate model in which the ocean and the land and atmosphere can inte… Source: El … Continue reading

Posted in AMETSOC, astrophysics, climate, climate change, climate models, computation, Dan Satterfield, differential equations, diffusion, diffusion processes, dynamical systems, ENSO, environment, forecasting, geophysics, global warming, Hyper Anthropocene, Kerry Emanuel, mathematics, maths, mesh models, meteorology, model comparison, NASA, NCAR, NOAA, numerical analysis, oceanography, physics, Principles of Planetary Climate, rationality, Ray Pierrehumbert, reasonableness, science, Spaceship Earth, stochastics, supercomputers, the right to know, thermodynamics, time series
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## “1D Wave with Delta Potential and Triangle Initial Position” (Jeff Galkowski, Stanford)

The latest calculations from Jeff Galkowski, of Stanford.

Posted in computation, engineering, Jeff Galkowski, mathematics, maths, McGill University, numerical analysis, numerical software, physics, proud dad, quantum, scattering, science, Stanford University, the right to know, University of California Berkeley, University of Rochester, wave equations, waves
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## STUFF IN PROGRESS

It’s a good time to reconnoiter and review the things I have in progress and are planned, both as a teaser, and as a promise. I am currently working the following technical projects, entirely on my personal time outside of … Continue reading

Posted in numerical analysis, planning, R, rationality, reasonableness, state-space models, statistics
2 Comments