Distributed Solar: The Democratizaton of Energy
Blogroll
- Woods Hole Oceanographic Institution (WHOI)
- Leadership lessons from Lao Tzu
- Pat's blog While it is described as “The mathematical (and other) thoughts of a (now retired) math teacher”, this is false humility, as it chronicles the present and past life and times of mathematicians in their context. Recommended.
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- American Statistical Association
- 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.
- James' Empty Blog
- Awkward Botany
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Carl Safina's blog One of the wisest on Earth
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- BioPython A collection of Python tools for quantitative Biology
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- Giant vertical monopolies for energy have stopped making sense
- Slice Sampling
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- 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
- 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.
- 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”
- Ives and Dakos techniques for regime changes in series
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- 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
- John Cook's reasons to use Bayesian inference
- 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/
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- "Perpetual Ocean" from NASA GSFC
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- NCAR AtmosNews
- 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
- Beautiful Weeds of New York City
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- Mertonian norms
- 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
- International Society for Bayesian Analysis (ISBA)
- 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.”
- Earle Wilson
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Mrooijer's Numbers R 4Us
- Gavin Simpson
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- Risk and Well-Being
- All about Sankey diagrams
- "Talking Politics" podcast David Runciman, Helen Thompson
- Healthy Home Healthy Planet
climate change
- 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.
- Dessler's 6 minute Greenhouse Effect video
- Sea Change Boston
- "When Did Global Warming Stop" Doc Snow’s treatment of the denier claim that there’s been no warming for the most recent N years. (See http://hubpages.com/@doc-snow for more on him.)
- Agendaists Eli Rabett’s coining of a phrase
- "Getting to the Energy Future We Want," Dr Steven Chu
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Risk and Well-Being
- Interview with Wally Broecker Interview with Wally Broecker
- 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
- RealClimate
- Climate Change Denying Organizations
- Climate at a glance Current state of the climate, from NOAA
- AIP's history of global warming science: impacts The American Institute of Physics has a fine history of the science of climate change. This link summarizes the history of impacts of climate change.
- 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
- NOAA Annual Greenhouse Gas Index report The annual assessment by the National Oceanic and Atmospheric Administration of the radiative forcing from constituent atmospheric greenhouse gases
- Berkeley Earth Surface Temperature
- Earth System Models
- The great Michael Osborne's latest opinions Michael Osborne is a genius operative and champion of solar energy. I have learned never to disregard ANYTHING he says. He is mentor of Karl Ragabo, and the genius instigator of the Texas renewable energy miracle.
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- 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
- "Climate science is setttled enough"
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- Wally Broecker on climate realism
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- "Mighty Microgrids" Webinar This is a Webinar on YouTube about Microgrids from the Institute for Local Self-Reliance (ILSR), featuring New York State and Minnesota
- The Keeling Curve The first, and one of the best programs for creating a spatially significant long term time series of atmospheric concentrations of CO2. Started amongst great obstacles by one, smart determined guy, Charles David Keeling.
- Nick Bower's "Scared Scientists"
- Climate impacts on retail and supply chains
- weather blocking patterns
- Exxon-Mobil statement on UNFCCC COP21
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- David Appell's early climate science
- 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.
- James Powell on sampling the climate consensus
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- Spectra Energy exposed
- 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
- Skeptical Science
- Andy Zucker's "Climate Change and Psychology"
- "A field guide to the climate clowns"
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- On Thomas Edison and Solar Electric Power
- Simple models of climate change
- 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.
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
Archives
Jan Galkowski
Category Archives: numerical algorithms
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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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.
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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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
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The Johnson-Lindenstrauss Lemma, and the paradoxical power of random linear operators. Part 1.
Updated, 2018-12-04 I’ll be discussing the ramifications of: William B. Johnson and Joram Lindenstrauss, “Extensions of Lipschitz mappings into a Hilbert space, Contemporary Mathematics, 26:189–206, 1984. for several posts here. Some introduction and links to proofs and explications will be … Continue reading
Posted in clustering, data science, dimension reduction, information theoretic statistics, Johnson-Lindenstrauss Lemma, k-NN, Locality Sensitive Hashing, mathematics, maths, multivariate statistics, non-parametric model, numerical algorithms, numerical linear algebra, point pattern analysis, random projections, recommender systems, science, stochastic algorithms, stochastics, subspace projection methods
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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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Fast means, fast moments (originally devised 1984)
(Updated 4th December 2018.) There are many devices available for making numerical calculations fast. Modern datasets and computational problems apply stylized architectures, and use approaches to problems including special algorithms for just calculating dominant eigenvectors or using non-classical statistical mechanisms … Continue reading
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
forecast for 27th March 2018
Today is the 21st of March, 2018. We are supposed to get our fourth nor’easter tomorrow this late Winter, and the third nor’easter in nearly as many weeks. ECMWF hosted, in this incarnation, at the Meteocentre UQAM in Montreal created … Continue reading
Posted in American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, AMETSOC, atmosphere, climate, climate change, climate disruption, climate education, climate models, coastal communities, ensemble methods, ensemble models, fluid dynamics, forecasting, global warming, Hyper Anthropocene, Mathematics and Climate Research Network, meteorological models, meteorology, numerical algorithms, physics, science, science education, spaghetti plots, tragedy of the horizon, water vapor
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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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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
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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ecoquant
667 per centimeter : climate science, quantitative biology, statistics, and energy policy 