Distributed Solar: The Democratizaton of Energy
Category Archives: model comparison
on turbulent eddies in oceans
Oceanic eddies are not negligible, especially in climate modeling. There’s the work of Dr Emily Shuckburgh of the BAS on this, but more specifically there’s section 6.3.3 of Gettelman and Rood, Demystifying Climate Models: A Users Guide to Earth System … 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
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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“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
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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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On friction and the duplicity
(Hat tip to Peter Sinclair at Climate Denial Crock of the Week.) Has Senator Cruz called Dr Carl Mears (video) of Remote Sensing Systems, the maker and interpreter of the sensor Senator Cruz used for his Spencer-Christy-Curry carnival? No. Of … Continue reading
Posted in AMETSOC, anemic data, Berkeley Earth Surface Temperature project, BEST, climate, climate change, climate data, climate disruption, confirmation bias, corruption, denial, disingenuity, ecology, evidence, fear uncertainty and doubt, geophysics, global warming, greenhouse gases, hiatus, Hyper Anthropocene, ignorance, meteorology, model comparison, NCAR, NOAA, obfuscating data, oceanography, physics, rationality, reasonableness, statistics, time series
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Not too shabby: “What’s warming the world” (Bloomberg Business), and “The siege of Miami” (The New Yorker)
What’s warming the world Infographic allowing the visitor to overlay time series of candidate causes for global warming, and thereby permitting them to draw their own conclusions. And Elizabeth Kolbert’s piece in The New Yorker, brings home the contradictions and … Continue reading
Posted in Anthropocene, business, climate change, climate data, climate zombies, complex systems, critical slowing down, denial, disingenuity, economics, environment, evidence, fossil fuels, global warming, greenhouse gases, Hyper Anthropocene, mitigation, model comparison, time series
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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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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
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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
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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
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Links explaining climate change Kevin Jones liked
Kevin Jones asked me if I could put the links in a Comment on a post I made at Google+ in a collection or something for reference. I am therefore repeating the Comment with these details below. No one simple … Continue reading
Posted in Anthropocene, astrophysics, bifurcations, biology, bridge to nowhere, carbon dioxide, chance, citizen science, citizenship, civilization, clean disruption, climate, climate change, climate disruption, climate education, climate models, climate zombies, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, dynamical systems, ecology, economics, efficiency, energy, energy reduction, environment, exponential growth, forecasting, fossil fuel divestment, fossil fuels, geophysics, global warming, history, investing, investment in wind and solar energy, IPCC, living shorelines, mass extinctions, mass transit, mathematics, maths, meteorology, methane, microgrids, model comparison, NASA, natural gas, NCAR, NOAA, oceanography, physics, politics, population biology, Principles of Planetary Climate, rationality, Ray Pierrehumbert, reasonableness, science, science education, Scripps Institution of Oceanography, sea level rise, sociology, solar power, statistics, temporal myopia, the right to know, Tony Seba, WHOI, wind power, zero carbon
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“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
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The CWSLab workflow tool: an experiment in community code development
Originally posted on Dr Climate:
Give anyone working in the climate sciences half a chance and they’ll chew your ear off about CMIP5. It’s the largest climate modelling project ever conducted and formed the basis for much of the IPCC…
Posted in climate, climate education, climate models, computation, differential equations, dynamical systems, environment, forecasting, geophysics, global warming, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, NCAR, oceanography, open source scientific software, physics, Principles of Planetary Climate, Python 3, rationality, reasonableness, science, science education, state-space models, statistics, time series, transparency
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We are trying. And the bitterest result is to have so-called colleagues align themselves with the Koch brothers
I attended a 350.org meeting tonight. One group A group presenting there called “Fighting Against Natural Gas” applauded themselves for assailing Senator Whitehouse of Rhode Island for his supportive position on natural gas pipelines. Now, I am no friend of … Continue reading
Posted in Anthropocene, astrophysics, Boston Ethical Society, bridge to nowhere, carbon dioxide, carbon dioxide sequestration, Carbon Tax, chemistry, citizenship, climate, climate change, climate education, consumption, decentralized electric power generation, demand-side solutions, ecology, economics, energy reduction, engineering, forecasting, fossil fuel divestment, investment in wind and solar energy, IPCC, JAGS, meteorology, methane, model comparison, NASA, natural gas, NCAR, Neill deGrasse Tyson, oceanography, open data, physics, politics, population biology, Principles of Planetary Climate, Python 3, R, rationality, reasonableness, reproducible research, risk, science, science education, Scripps Institution of Oceanography
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Richard Muller: “I Was Wrong On Global Warming, But It Didn’t Convince The ‘Sceptics'”
Update. 26th February 2015 This is not directly related to the BEST project described in the YouTube video above, but the Berkeley National Laboratory has experimentally linked increases in radiative forcing with increases in atmospheric concentrations of CO2 due to … Continue reading
Posted in astrophysics, Bayes, carbon dioxide, citizenship, civilization, climate, climate change, climate education, differential equations, ecology, environment, geoengineering, geophysics, IPCC, mathematics, maths, meteorology, model comparison, NASA, NCAR, NOAA, oceanography, physics, population biology, rationality, Ray Pierrehumbert, reasonableness, reproducible research, risk, science, science education, sea level rise, the right to know
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Models don’t over-estimate warming?
Originally posted on …and Then There's Physics:
I thought I might write about the new paper by Jochem Marotzke and Piers Forster called Forcing, feedback and internal variability in global temperature trends. It’s already been discussed in a Carbon…
Posted in astrophysics, carbon dioxide, chemistry, citizen science, citizenship, civilization, climate, climate change, climate education, differential equations, diffusion processes, ecology, education, energy, forecasting, geophysics, IPCC, mathematics, meteorology, model comparison, NASA, NCAR, NOAA, oceanography, physics, Principles of Planetary Climate, rationality, Ray Pierrehumbert, reasonableness, science, statistics, the right to know
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engineering and understanding with stable models
Stable distributions or Lévy -stable models is a class of probability distributions which contains the Gaussian, the Cauchy (or Lorentz), and the Lévy distribution. They are parameterized by an which is . Values of of 1 or less give distributions … Continue reading
Posted in approximate Bayesian computation, Bayesian, citizen science, climate, climate change, climate education, differential equations, diffusion processes, ecology, economics, forecasting, geophysics, information theoretic statistics, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, NOAA, oceanography, physics, rationality, reasonableness, risk, science, science education, stochastic search, the right to know
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Naomi Oreskes and significance testing
Naomi Oreskes has an op-ed in The New York Times today, which intends to defend the severe standards of evidence scientists employ, with special applicability to climate science and their explanation of causation (greenhouse gases produce radiative forcing), attribution (most … Continue reading
“[W]e want to model the process as we would simulate it.”
Professor Darren Wilkinson offers a pithy insight on how to go about constructing statistical models, notably hierarchical ones: “… we want to model the process as we would simulate it ….” This appears in his blog post One-way ANOVA with … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, ecology, engineering, forecasting, mathematics, mathematics education, maths, model comparison, optimization, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, sociology, statistics, stochastic algorithms
Tagged ANOVA
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struggling with problems already partly solved by others
Climate modelers and models see as their frontier the problem of dealing with spontaneous dynamics in systems such as atmosphere or ocean which are not directly forced by boundary conditions such as radiative forcing due to increased greenhouse gas (“GHG”) … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, climate, climate education, differential equations, ecology, engineering, environment, geophysics, IPCC, mathematics, mathematics education, meteorology, model comparison, NCAR, NOAA, oceanography, physics, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, statistics, stochastic algorithms, stochastic search
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“… making a big assumption …”
“That’s making a big assumption.” (This post is a follow-on from an earlier one.) In the colloquial, the phrase means basing an argument on a precondition which is unusual or atypical or offends common sense. When applied to scientific hypotheses, … Continue reading
