### Distributed Solar: The Democratizaton of Energy

### Blogroll

- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- Karl Broman
- All about ENSO, and lunar tides (Paul Pukite) Historically, ENSO has been explained in terms of winds. But recently — and Dr Paul Pukite has insisted upon this for a long time — the oscillation of ENSO has been explained as a large-scale slosh due to lunar tidal forcing.
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- Comprehensive Guide to Bayes Rule
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- "Talking Politics" podcast David Runciman, Helen Thompson
- "The Expert"
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- Darren Wilkinson's introduction to ABC Darren Wilkinson’s introduction to approximate Bayesian computation (“ABC”). See also his post about summary statistics for ABC https://darrenjw.wordpress.com/2013/09/01/summary-stats-for-abc/
- Awkward Botany
- London Review of Books
- Mrooijer's Numbers R 4Us
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- Mike Bloomberg, 2020 He can get progress on climate done, has the means and experts to counter the Trump and Republican digital disinformation machine, and has the experience, knowledge, and depth of experience to achieve and unify.
- Why It’s So Freaking Hard To Make A Good COVID-19 Model Five Thirty Eight’s take on why pandemic modeling is so difficult
- Hermann Scheer Hermann Scheer was a visionary, a major guy, who thought deep thoughts about energy, and its implications for humanity’s relationship with physical reality
- Dollars per BBL: Energy in Transition
- Slice Sampling
- Label Noise
- Healthy Home Healthy Planet
- The Alliance for Securing Democracy dashboard
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- SASB Sustainability Accounting Standards Board
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- Tony Seba Solar energy, electric vehicle, energy storage, and business disruption professor and visionary
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- Higgs from AIR describing NAO and EA Stephanie Higgs from AIR Worldwide gives a nice description of NAO and EA in the context of discussing “The Geographic Impact of Climate Signals on European Winter Storms”
- Dr James Spall's SPSA
- Ted Dunning
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- Ives and Dakos techniques for regime changes in series
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- Logistic curves in market disruption From DollarsPerBBL, about logistic or S-curves as models of product take-up rather than exponentials, with notes on EVs
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- American Association for the Advancement of Science (AAAS)
- Gavin Simpson
- Leverhulme Centre for Climate Change Mitigation
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- What If
- John Cook's reasons to use Bayesian inference
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- All about Sankey diagrams
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”

### climate change

- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- Earth System Models
- The beach boondoggle Prof Rob Young on how owners of beach property are socializing their risks at costs to all of us, not the least being it seems coastal damage is less than it actually is
- Model state level energy policy for New Englad Bob Massie’s proposed energy policy for Massachusetts, an admirable model for energy policy anywhere in New England
- SolarLove
- Jacobson WWS literature index
- Tell Utilities Solar Won't Be Killed Barry Goldwater, Jr’s campaign to push for solar expansion against monopolistic utilities, as a Republican
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- And Then There's Physics
- weather blocking patterns
- Sea Change Boston
- "Getting to the Energy Future We Want," Dr Steven Chu
- Skeptical Science
- World Weather Attribution
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- The Scientific Case for Modern Human-caused Global Warming
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- CLIMATE ADAM Previously from the Science news staff at the podcast of Nature (“Nature Podcast”), the journal, now on YouTube, encouraging climate action through climate comedy.
- Transitioning to fully renewable energy Professor Saul Griffiths talks to transitioning the customer journey, from a dependency upon fossil fuels to an electrified future
- The Sunlight Economy
- Mrooijer's Global Temperature Explorer
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- Spectra Energy exposed
- Grid parity map for Solar PV in United States
- Dessler's 6 minute Greenhouse Effect video
- US$165/tonne CO2: Sweden Sweden has a Carbon Dioxide tax of US$165 per tonne at present. CO2 tax was imposed in 1991. GDP has grown 60%.
- Paul Beckwith Professor Beckwith is, in my book, one of the most insightful and analytical observers on climate I know. I highly recommend his blog, and his other informational products.
- Andy Zucker's "Climate Change and Psychology"
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- Thriving on Low Carbon
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- “Ways to [try to] slow the Solar Century''
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- "Warming Slowdown?" (part 1 of 2) The idea of a global warming slowdown or hiatus is critically examined, emphasizing the literature, the datasets, and means and methods for telling such. In two parts.
- Climate Change Denying Organizations
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- History of discovering Global Warming From the American Institute of Physics.
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Climate model projections versus observations
- David Appell's early climate science
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- Climate impacts on retail and supply chains
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- Climate change: Evidence and causes A project of the UK Royal Society: (1) Answers to key questions, (2) evidence and causes, and (3) a short guide to climate science

### Archives

### Jan Galkowski

# Category Archives: model-free forecasting

## Phase Plane plots of COVID-19 deaths *with uncertainties*

I. Introduction. It’s time to fulfill the promise made in “Phase plane plots of COVID-19 deaths“, a blog post from 2nd May 2020, and produce the same with uncertainty clouds about the functional trajectories(*). To begin, here are some assumptions … Continue reading

Posted in American Statistical Association, Andrew Harvey, anomaly detection, count data regression, COVID-19, dependent data, dlm package, Durbin and Koopman, dynamic linear models, epidemiology, filtering, forecasting, Kalman filter, LaTeX, model-free forecasting, Monte Carlo Statistical Methods, numerical algorithms, numerical linear algebra, population biology, population dynamics, prediction, R, R statistical programming language, regression, statistical learning, stochastic algorithms
Tagged prediction intervals
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## Calculating Derivatives from Random Forests

(Comment on prediction intervals for random forests, and links to a paper.) (Edits to repair smudges, 2020-06-28, about 0945 EDT. Closing comment, 2020-06-30, 1450 EDT.) There are lots of ways of learning about mathematical constructs, even about actual machines. One … Continue reading

Posted in bridge to somewhere, Calculus, dependent data, dynamic generalized linear models, dynamical systems, ensemble methods, ensemble models, filtering, forecasting, hierarchical clustering, linear regression, model-free forecasting, Monte Carlo Statistical Methods, non-mechanistic modeling, non-parametric model, non-parametric statistics, numerical algorithms, prediction, R statistical programming language, random forests, regression, sampling, splines, statistical learning, statistical series, statistics, time derivatives, time series
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## What happens when time sampling density of a series matches its growth

This is the newly updated map of COVID-19 cases in the United States, updated, presumably, because of the new emphasis upon testing: How do we know this is the recent of recent testing? Look at the map of active cases: … Continue reading

Posted in American Association for the Advancement of Science, American Statistical Association, anti-intellectualism, anti-science, climate denial, corruption, data science, data visualization, Donald Trump, dump Trump, epidemiology, experimental science, exponential growth, forecasting, Kalman filter, model-free forecasting, nonlinear systems, open data, penalized spline regression, population dynamics, sampling algorithms, statistical ecology, statistical models, statistical regression, statistical series, statistics, sustainability, the right to know, the stack of lies
1 Comment

## A response to a post on *RealClimate*

(Updated 2342 EDT, 28 June 2019.) This is a response to a post on RealClimate which primarily concerned economist Ross McKitrick’s op-ed in the Financial Post condemning the geophysical community for disregarding Roger Pielke, Jr’s arguments. Pielke, in that link, … Continue reading

Posted in American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, AMETSOC, Bayesian, climate change, ecology, Ecology Action, environment, evidence, experimental design, Frequentist, global warming, Hyper Anthropocene, machine learning, model comparison, model-free forecasting, multivariate statistics, science, science denier, statistical series, statistics, time series
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## Stream flow and P-splines: Using built-in estimates for smoothing

Mother Brook in Dedham Massachusetts was the first man-made canal in the United States. Dug in 1639, it connects the Charles River at Dedham, to the Neponset River in the Hyde Park section of Boston. It was originally an important … Continue reading

Posted in American Statistical Association, citizen data, citizen science, Clausius-Clapeyron equation, Commonwealth of Massachusetts, cross-validation, data science, dependent data, descriptive statistics, dynamic linear models, empirical likelihood, environment, flooding, floods, Grant Foster, hydrology, likelihood-free, meteorological models, model-free forecasting, non-mechanistic modeling, non-parametric, non-parametric model, non-parametric statistics, numerical algorithms, precipitation, quantitative ecology, statistical dependence, statistical series, stream flow, Tamino, the bootstrap, time series, water vapor
2 Comments

## Series, symmetrized Normalized Compressed Divergences and their logit transforms

(Major update on 11th January 2019. Minor update on 16th January 2019.) On comparing things The idea of a calculating a distance between series for various purposes has received scholarly attention for quite some time. The most common application is … Continue reading

Posted in Akaike Information Criterion, bridge to somewhere, computation, content-free inference, data science, descriptive statistics, divergence measures, engineering, George Sughihara, information theoretic statistics, likelihood-free, machine learning, mathematics, model comparison, model-free forecasting, multivariate statistics, non-mechanistic modeling, non-parametric statistics, numerical algorithms, statistics, theoretical physics, thermodynamics, time series
4 Comments

## climate model democracy

“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

Posted in American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, AMETSOC, Anthropocene, attribution, Bayesian model averaging, Bloomberg, citizen science, climate, climate business, climate change, climate data, climate disruption, climate education, climate justice, Climate Lab Book, climate models, coastal communities, coastal investment risks, complex systems, differential equations, disruption, dynamic linear models, dynamical systems, ecology, emergent organization, ensemble methods, ensemble models, ensembles, Eric Rignot, evidence, fear uncertainty and doubt, FEMA, forecasting, free flow of labor, global warming, greenhouse gases, greenwashing, Humans have a lot to answer for, Hyper Anthropocene, Jennifer Francis, Joe Romm, Kevin Anderson, Lévy flights, LBNL, leaving fossil fuels in the ground, liberal climate deniers, mathematics, mathematics education, model-free forecasting, multivariate adaptive regression splines, National Center for Atmospheric Research, obfuscating data, oceanography, open source scientific software, optimization, perceptrons, philosophy of science, phytoplankton
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## 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

## What are the odds of net zero?

What’s the Question? A question was posed by a colleague a couple of months ago: What are the odds of a stock closing at the same price it opened? I found the question interesting, because, at first, it appeared to … Continue reading

## Eli on “Tom [Karl]’s trick and experimental design“

A very fine post at Eli’s blog for students of statistics, meteorology, and climate (like myself) titled: Tom’s trick and experimental design Excerpt: This and the graph from Menne at the top shows that Karl’s trick is working. Although we … Continue reading

Posted in American Meteorological Association, American Statistical Association, AMETSOC, anomaly detection, climate, climate change, climate data, data science, evidence, experimental design, generalized linear mixed models, GISTEMP, GLMMs, global warming, model comparison, model-free forecasting, reblog, sampling, sampling networks
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## “Hurricanes, Sea Level, and Baloney” (from Tamino)

Originally posted on Open Mind:

WUWT has a post in which Neil Frank proclaims that Hillary Clinton is no hurricane expert but he is. (Frank’s post was originally published on The Daily Caller, but was reprinted on WUWT with permission.)…

## 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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## “All models are wrong. Some models are useful.” — George Box

(Image courtesy of the Damien Garcia.) As a statistician and quant, I’ve thought hard about that oft-cited Boxism. I’m not sure I agree. It’s not that there is such a thing as a perfect model, or correct model, whatever in … Continue reading

Posted in abstraction, American Association for the Advancement of Science, astronomy, astrophysics, mathematics, model-free forecasting, numerics, perceptions, physical materialism, physics, rationality, reason, reasonableness, science, spatial statistics, splines, statistics, the right to know, theoretical physics, time series
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## Carbon Sinks in Crisis — It Looks Like the World’s Largest Rainforest is Starting to Bleed Greenhouse Gasses

Originally posted on robertscribbler:

Back in 2005, and again in 2010, the vast Amazon rainforest, which has been aptly described as the world’s lungs, briefly lost its ability to take in atmospheric carbon dioxide. Its drought-stressed trees were not growing…

Posted in bifurcations, carbon dioxide, carbon dioxide sequestration, changepoint detection, climate, climate change, climate disruption, disruption, dynamical systems, environment, exponential growth, fossil fuels, geophysics, global warming, IPCC, Lévy flights, Lorenz, Minsky moment, model-free forecasting, physics, population biology, population dynamics, Principles of Planetary Climate, quantitative biology, quantitative ecology, random walk processes, Ray Pierrehumbert, reason, reasonableness, regime shifts, risk, Stefan Rahmstorf, the right to be and act stupid, the tragedy of our present civilization, UU Humanists
2 Comments

## 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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