Distributed Solar: The Democratizaton of Energy
Blogroll
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- Prediction vs Forecasting: Knaub “Unfortunately, ‘prediction,’ such as used in model-based survey estimation, is a term that is often subsumed under the term ‘forecasting,’ but here we show why it is important not to confuse these two terms.”
- NCAR AtmosNews
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- Risk and Well-Being
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- International Society for Bayesian Analysis (ISBA)
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- In Monte Carlo We Trust The statistics blog of Matt Asher, actually called the “Probability and Statistics Blog”, but his subtitle is much more appealing. Asher has a Manifesto at http://www.statisticsblog.com/manifesto/.
- Ives and Dakos techniques for regime changes in series
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Mrooijer's Numbers R 4Us
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- Woods Hole Oceanographic Institution (WHOI)
- "The Expert"
- American Statistical Association
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- 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
- 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/
- American Association for the Advancement of Science (AAAS)
- Gabriel's staircase
- 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.
- All about Sankey diagrams
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Earle Wilson
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- distributed solar and matching location to need
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- BioPython A collection of Python tools for quantitative Biology
- John Cook's reasons to use Bayesian inference
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- Comprehensive Guide to Bayes Rule
- Carl Safina's blog One of the wisest on Earth
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- SASB Sustainability Accounting Standards Board
- Dollars per BBL: Energy in Transition
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- Busting Myths About Heat Pumps Heat pumps are perhaps the most efficient heating and cooling systems available. Recent literature distributed by utilities hawking natural gas and other sources use performance figures from heat pumps as they were available 15 years ago. See today’s.
- Number Cruncher Politics
- All about models
- Los Alamos Center for Bayesian Methods
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Tim Harford's “More or Less'' Tim Harford explains – and sometimes debunks – the numbers and statistics used in political debate, the news and everyday life
- Leadership lessons from Lao Tzu
- Karl Broman
- "Talking Politics" podcast David Runciman, Helen Thompson
climate change
- Agendaists Eli Rabett’s coining of a phrase
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- Social Cost of Carbon
- An open letter to Steve Levitt
- "Getting to the Energy Future We Want," Dr Steven Chu
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- Climate Change Denying Organizations
- Documenting the Climate Deniarati at work
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- Tell Utilities Solar Won't Be Killed Barry Goldwater, Jr’s campaign to push for solar expansion against monopolistic utilities, as a Republican
- Climate impacts on retail and supply chains
- 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%.
- Berkeley Earth Surface Temperature
- Skeptical Science
- 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
- weather blocking patterns
- Simple models of climate change
- "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.
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- “Ways to [try to] slow the Solar Century''
- Bloomberg interactive graph on “What's warming the world''
- Mrooijer's Global Temperature Explorer
- The Green Plate Effect Eli Rabett’s “The Green Plate Effect”
- Steve Easterbrook's excellent climate blog: See his "The Internet: Saving Civilization or Trashing the Planet?" for example Heavy on data and computation, Easterbrook is a CS prof at UToronto, but is clearly familiar with climate science. I like his “The Internet: Saving Civilization or Trashing the Planet” very much.
- Sea Change Boston
- Jacobson WWS literature index
- 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.
- Dessler's 6 minute Greenhouse Effect video
- Reanalyses.org
- Spectra Energy exposed
- Climate Change Reports By John and Mel Harte
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Andy Zucker's "Climate Change and Psychology"
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- "Betting strategies on fluctuations in the transient response of greenhouse warming" By Risbey, Lewandowsky, Hunter, Monselesan: Betting against climate change on durations of 15+ years is no longer a rational proposition.
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- "A field guide to the climate clowns"
- World Weather Attribution
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- "Climate science is setttled enough"
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- Jacobson WWS literature index
- 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
- RealClimate
- MIT's Climate Primer
- Mathematics and Climate Research Network The Mathematics and Climate Research Network (MCRN) engages mathematicians to collaborating on the cryosphere, conceptual model validation, data assimilation, the electric grid, food systems, nonsmooth systems, paleoclimate, resilience, tipping points.
- Climate Change: A health emergency … New England Journal of Medicine Caren G. Solomon, M.D., M.P.H., and Regina C. LaRocque, M.D., M.P.H., January 17, 2019 N Engl J Med 2019; 380:209-211 DOI: 10.1056/NEJMp1817067
- The Scientific Case for Modern Human-caused Global Warming
Archives
Jan Galkowski
Category Archives: dynamic linear models
Baseload is an intellectual crutch for engineers and utility managers who cannot think dynamically
This is an awesome presentation by Professor Joshua Pearce of Michigan Technological University. (h/t Peter Sinclair’s Climate Denial Crock of the Week) The same idea, that “baseload is a shortcut for engineers who can’t think dynamically”, was similar in the … Continue reading
Posted in American Solar Energy Society, an ignorant American public, Bloomberg Green, Bloomberg New Energy Finance, bridge to somewhere, CleanTechnica, control theory, controls theory, decentralized electric power generation, decentralized energy, differential equations, dynamic linear models, dynamical systems, electrical energy engineering, electrical energy storage, electricity, Kalman filter, optimization, photovoltaics, rate of return regulation, solar domination, solar energy, solar revolution, stochastic algorithms, utility company death spiral, wind energy, wind power, zero carbon
Tagged baseload, controls theory, dynamics, electrical engineering, energy storage, marginal cost of energy, solar energy, wind energy
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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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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
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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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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''
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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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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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Six cases of models
The previous post included an attempt to explain land surface temperatures as estimated by the BEST project using a dynamic linear model including regressions on both quarterly CO2 concentrations and ocean heat content. The idea was to check the explanatory … Continue reading
Posted in AMETSOC, anemic data, Anthropocene, astrophysics, Bayesian, Berkeley Earth Surface Temperature project, BEST, carbon dioxide, climate, climate change, climate data, climate disruption, climate models, dlm package, dynamic linear models, dynamical systems, environment, fossil fuels, geophysics, Giovanni Petris, global warming, greenhouse gases, Hyper Anthropocene, information theoretic statistics, maths, maximum likelihood, meteorology, model comparison, numerical software, Patrizia Campagnoli, Rauch-Tung-Striebel, Sonia Petrone, state-space models, stochastic algorithms, stochastic search, SVD, time series
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“The Myth of the 1970s Global Cooling Consensus”
“The Myth of the 1970s Global Cooling Scientific Consensus“, T. C. Peterson, W. M. Connolley, J. Fleck, http://dx.doi.org/10.1175/2008BAMS2370.1. Abstract Climate science as we know it today did not exist in the 1960s and 1970s. The integrated enterprise embodied in the … Continue reading
Posted in AMETSOC, Anthropocene, carbon dioxide, citizen science, climate, climate change, climate data, climate disruption, climate education, climate zombies, coastal communities, differential equations, dynamic linear models, dynamical systems, ecology, environment, fluid dynamics, fossil fuel divestment, fossil fuels, geophysics, global warming, greenhouse gases, Hyper Anthropocene, ice sheet dynamics, investing
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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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dynamic linear model applied to sea-level-rise anomalies
I spent much of the data working up a function for level+trend dynamic linear modeling based upon the dlm package by Petris, Petrone, and Campagnoli, while trying some calculations and code for regime shift detection. One of the test cases … Continue reading
Posted in Bayesian, citizen science, climate change, climate data, climate disruption, dynamic linear models, floods, forecasting, Frequentist, global warming, icesheets, information theoretic statistics, Kalman filter, meteorology, open data, sea level rise, state-space models, statistics, time series
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“The storage necessity myth: how to choreograph high-renewables electricity systems”
(This was originally presented by CleanTechMedia.) Sounds like a great role for smart control systems. Flash COP21 won’t matter. Listen to Professor Tony Seba. (Use your browser Back button to return to this blog.) Excerpt: Clearly, though, many vested interests … Continue reading
Posted in adaptation, Anthropocene, Cape Wind, Carbon Tax, citizenship, clean disruption, climate change, climate disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, denial, dynamic linear models, dynamical systems, economics, efficiency, energy, energy reduction, energy utilities, engineering, fear uncertainty and doubt, forecasting, fossil fuel divestment, fossil fuels, global warming, Hyper Anthropocene, ignorance, investment in wind and solar energy, meteorology, microgrids, natural gas, obfuscating data, planning, politics, public utility commissions, PUCs, rationality, reasonableness, Sankey diagram, solar energy, solar power, SolarPV.tv, Stanford University, sustainability, the right to know, Tony Seba, University of California Berkeley, wind energy, wind power, zero carbon
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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
Is Earth Much More Sensitive to CO2 Than Thought?
Originally posted on Climate Denial Crock of the Week:
A nahcolite from the Eocene Green River Formation. Credit: Timothy Lowenstein Phys.org: Ancient climates on Earth may have been more sensitive to carbon dioxide than was previously thought, according to new…
Posted in Anthropocene, Carbon Cycle, carbon dioxide, climate, climate change, climate data, climate disruption, differential equations, diffusion processes, dynamic linear models, dynamical systems, environment, fossil fuels, generalized linear models, geophysics, global warming, Hyper Anthropocene, Principles of Planetary Climate, risk, science
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Southern Oscillation (SOI) correlated with Outgoing Longwave Radiation (OLR)
To the climate community this is nothing at all new, but I spotted these time series today and thought they would make a nice exhibit on how something people have direct control over, greenhouse gas emissions, affect a “teleconnection mechanism” … Continue reading
Posted in AMETSOC, bifurcations, carbon dioxide, climate, climate change, climate disruption, climate models, Dan Satterfield, differential equations, dynamic linear models, dynamical systems, ENSO, environment, forecasting, generalized linear models, geophysics, global warming, greenhouse gases, IPCC, Mathematica, mathematics, maths, meteorology, NCAR, NOAA, numerical software, oceanography, open data, physics, population biology, Principles of Planetary Climate, rationality, reasonableness, science, Spaceship Earth, state-space models, thermodynamics, time series
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On differential localization of tumors using relative concentrations of ctDNA. Part 1.
Like most mammalian tissue, tumors often produce shards of DNA as a byproduct of cell death and fracture. This circulating tumor DNA is being studied as a means of detecting tumors or their resurgence after treatment. (See also a Q&A … Continue reading
Posted in approximate Bayesian computation, Bayesian, Bayesian inversion, cardiovascular system, diffusion, dynamic linear models, eigenanalysis, engineering, forecasting, mathematics, maths, medicine, networks, prediction, spatial statistics, statistics, stochastic algorithms, stochastic search, wave equations
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On Changing Things
You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete. That’s from Buckminster Fuller, a fellow Unitarian.
Posted in adaptation, Anthropocene, bifurcations, bridge to nowhere, Buckminster Fuller, Cauchy distribution, clean disruption, climate disruption, demand-side solutions, destructive economic development, Disney, dynamic linear models, dynamical systems, Epcot, exponential growth, fossil fuel divestment, global warming, Hyper Anthropocene, physical materialism, planning, rationality, reasonableness, Spaceship Earth, stochastic algorithms
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Solar array with cloud predicting technology launched in WA
Australia’s first grid-connected solar power project with cloud predicting technology launched at Karratha Airport, WA, in bid to smooth solar supply. Source: Solar array with cloud predicting technology launched in WA
Posted in adaptation, Anthropocene, carbon dioxide, citizenship, civilization, clean disruption, climate, climate change, climate disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, dynamic linear models, efficiency, energy, energy reduction, energy utilities, engineering, environment, ethics, forecasting, geophysics, global warming, Hyper Anthropocene, investment in wind and solar energy, Kalman filter, mathematics, maths, meteorology, microgrids, mitigation, NCAR, numerical software, optimization, physics, prediction, probabilistic programming, rationality, reasonableness, risk, science, solar power, stochastics, sustainability, time series
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Utilities for dummies: How they work and why that needs to change (from grist.org)
“Utilities are shielded by a force field of tedium.” “Solar panels could destroy U.S. utilities, according to U.S. utilities.” Utilities for dummies: How they work and why that needs to change“, a compact introduction, from grist.org. And there’s an additional … Continue reading
Posted in Anthropocene, bifurcations, bridge to nowhere, carbon dioxide, citizenship, civilization, clean disruption, climate, climate change, climate disruption, climate education, conservation, consumption, corruption, decentralized electric power generation, decentralized energy, demand-side solutions, destructive economic development, disingenuity, dynamic linear models, dynamical systems, ecology, economics, education, efficiency, energy, energy reduction, energy utilities, engineering, environment, ethics, exponential growth, finance, forecasting, fossil fuel divestment, fossil fuels, fracking, global warming, Hyper Anthropocene, ignorance, investing, investment in wind and solar energy, mathematics, maths, meteorology, methane, microgrids, natural gas, optimization, physics, pipelines, politics, prediction, public utility commissions, PUCs, rationality, reasonableness, risk, science, solar power, statistics, sustainability, taxes, temporal myopia, the right to know, time series, Tony Seba, wind power, zero carbon
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Solar installation progress, courtesy of MacSolarIndex.com
The MAC Solar Index tracks a set of solar manufacturing and installation companies. It is also the basis for the Guggenheim Investments “TAN” Exchange-Traded Fund (“ETF”, *). They recently published a progress report on global solar installations, which I wanted … Continue reading
Posted in adaptation, Anthropocene, carbon dioxide, citizen science, citizenship, civilization, clean disruption, climate, climate change, climate data, climate disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, destructive economic development, dynamic linear models, dynamical systems, ecology, economics, efficiency, energy, energy reduction, environment, exponential growth, forecasting, fossil fuel divestment, fossil fuels, geophysics, global warming, Hyper Anthropocene, investing, investment in wind and solar energy, mathematics, mathematics education, maths, meteorology, microgrids, open data, optimization, physics, politics, prediction, rationality, reasonableness, risk, science, science education, solar power, sustainability, the right to know, time series, Tony Seba, wind power, zero carbon
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SCIENCE OF DOOM takes on assessing zero Carbon power and a zero Carbon grid
Updated, 2127 EDT, 10th August 2015 The blog, Science of Doom, has taken on a new thread discussing the technical feasibilities and problems associated with building out zero Carbon energy in the context of an electric grid. As such, it … Continue reading
Posted in adaptation, Anthropocene, clean disruption, climate data, climate disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, destructive economic development, dynamic linear models, dynamical systems, economics, efficiency, energy, energy reduction, engineering, environment, exponential growth, forecasting, fossil fuel divestment, global warming, Hyper Anthropocene, investing, investment in wind and solar energy, microgrids, open data, optimization, prediction, rationality, reasonableness, risk, solar power, state-space models, stochastics, sustainability, the right to know, time series, wind power, Wordpress, zero carbon
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Comprehensive and compact tutorial on Petris’ DLM package in R; with an update about Helske’s KFAS
A blogger named Lalas produced on Quantitative Thoughts a very comprehensive and compact tutorial on the R package dlm by Petris. I use dlm a lot. Unfortunately, Lalas does not give details on how the SVD is used. They do … Continue reading
Posted in Bayes, Bayesian, dynamic linear models, dynamical systems, forecasting, Kalman filter, mathematics, maths, multivariate statistics, numerical software, open source scientific software, prediction, R, Rauch-Tung-Striebel, state-space models, statistics, stochastic algorithms, SVD, time series
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ecoquant
667 per centimeter : climate science, quantitative biology, statistics, and energy policy 