Category Archives: differential equations

Sea Surface Anomalies

(Hat tip to Susan Stone.) The graphic below shows sea surface temperature anomalies relative to the 1971-2000 baseline First data are courtesy of the Climate Reanalyzer, a joint project of the Climate Change Institute at the University of Maine, and … Continue reading

Posted in Anthropocene, carbon dioxide, climate, climate change, climate disruption, climate education, differential equations, diffusion processes, dynamical systems, ecology, ENSO, environment, forecasting, geophysics, global warming, Hyper Anthropocene, IPCC, mathematics, MCMC, NASA, NCAR, NOAA, oceanography, open data, physics, Principles of Planetary Climate, rationality, reasonableness, risk, science, science education, sea level rise, statistics, sustainability, the right to know, time series, transparency | 1 Comment

“Regulating Government”, from Overcoming Bias

Regulating Government. This post is about governments — with the advice of big banks — gaming pension accounts so they appear more solvent than they are.

Posted in differential equations, diffusion processes, dynamical systems, economics, finance, risk, statistics, taxes, the right to know, time series | Leave a comment

“Why Using El Nino to Forecast the Winter is Risky” – Dan’s Wild Wild Science Journal

Why Using El Nino to Forecast the Winter is Risky – Dan's Wild Wild Science Journal – AGU Blogosphere.

Posted in chance, climate models, differential equations, dynamical systems, ensembles, ENSO, environment, forecasting, geophysics, history, mathematics, meteorology, NCAR, NOAA, nor'easters, oceanography, physics, risk, science, statistics | Leave a comment

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 | Leave a comment

“Feedback temperature dependence determines the risk of high warming”

Jonah Bloch-Johnson, Ray Pierrehumbert, and Dorian Abbot have a new paper out in Geophysical Research Letters which is pretty exciting, at least for me, having to do with both climate and dynamical systems. They are far from the only ones … Continue reading

Posted in bifurcations, Cauchy distribution, chance, climate, climate change, climate disruption, climate education, differential equations, dynamical systems, ecology, environment, forecasting, geophysics, global warming, mathematics, maths, meteorology, physics, Principles of Planetary Climate, rationality, Ray Pierrehumbert, science | Leave a comment

Warming is proportional to CUMULATIVE CARBON EMISSIONS, not emission intensity

Highlighting the key parts of the Abstract of this very important paper below: The global temperature response to increasing atmospheric CO2 is often quantified by metrics such as equilibrium climate sensitivity and transient climate response1. These approaches, however, do not … Continue reading

Posted in astrophysics, carbon dioxide, climate, climate change, climate education, consumption, differential equations, ecology, engineering, environment, forecasting, geophysics, IPCC, mathematics, maths, meteorology, oceanography, physics, Principles of Planetary Climate, reasonableness, risk, science | 1 Comment

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 | Leave a comment

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 | 1 Comment

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 | Leave a comment

The designers of our climate

Originally posted on …and Then There's Physics:
Okay, I finally succumbed and actually waded through some of the new paper by Monckton, Soon, Legates & Briggs called Why models run hot: results from an irreducibly simple climate model. I…

Posted in astrophysics, bridge to nowhere, carbon dioxide, carbon dioxide capture, carbon dioxide sequestration, Carbon Tax, Carl Sagan, citizenship, civilization, climate, climate change, climate education, differential equations, ecology, economics, engineering, environment, ethics, forecasting, fossil fuel divestment, geoengineering, geophysics, humanism, IPCC, mathematics, mathematics education, maths, meteorology, methane, NASA, NCAR, Neill deGrasse Tyson, NOAA, oceanography, open data, open source scientific software, physics, politics, population biology, Principles of Planetary Climate, probabilistic programming, R, rationality, reasonableness, reproducible research, risk, science, science education, scientific publishing, sociology, solar power, statistics, testing, the right to know | 1 Comment

“Atmospheric lifetime of fossil fuel carbon dioxide” (2009)

These basic facts do not appear to be widely known, so it’s a good thing this classic paper is now available in a new, easily accessible form. David Archer, Michael Eby, Victor Brovkin, Andy Ridgwell, Long Cao, Uwe Mikolajewicz, Ken … Continue reading

Posted in astrophysics, carbon dioxide, carbon dioxide capture, carbon dioxide sequestration, Carbon Tax, chemistry, citizenship, civilization, climate, climate education, conservation, consumption, demand-side solutions, differential equations, ecology, economics, education, energy, energy reduction, engineering, environment, fossil fuel divestment, geoengineering, geophysics, IPCC, meteorology, methane, natural gas, NCAR, NOAA, oceanography, physics, Principles of Planetary Climate, rationality, reasonableness, risk, science, science education | 2 Comments

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 | 1 Comment

Understanding mechanisms in climate over short periods and in local regions

This is interesting, because it shows how any particular observational history of Earth is one election of a large number of possible futures. This is exactly the same point made by Slava Kharin in his 2008 tutorial lecture “Statistical concepts … Continue reading

Posted in carbon dioxide, climate, climate education, differential equations, ecology, energy, environment, forecasting, geophysics, IPCC, mathematics, mathematics education, maths, meteorology, NCAR, NOAA, oceanography, physics, rationality, reasonableness, science, statistics, stochastic algorithms | 2 Comments

“Can we trust climate models?”

J. C. Hargreaves, J. D. Annan, “Can we trust climate models?”, WIREs Climate Change 2014, 5:435–440. doi: 10.1002/wcc.288. See also D. A. Stainforth, T. Aina, C. Christensen, M. Collins, N. Faull, D. J. Frame, J. A. Kettleborough, S. Knight, A. … Continue reading

Posted in Bayes, Bayesian, climate, climate education, differential equations, ecology, forecasting, geophysics, IPCC, mathematics education, meteorology, NCAR, NOAA, physics, rationality, reasonableness, risk, science, science education, statistics, stochastic algorithms | 1 Comment

Climate Variability Diagnostics Package

NCAR’s CVDP, just written up in AGU’s EOS. The purpose, and links. The talk. Nicely done test engineering effort.

Posted in climate, differential equations, engineering, environment, geophysics, mathematics, maths, meteorology, NCAR, NOAA, physics, science, statistics, testing | Leave a comment

El Nino, the scientific story (by Daniel Gross)

A scientific detective story. El Niño. How in the world did they figure that out? “Fishing in pink waters: How scientists unraveled the El Niño mystery“. By Daniel Gross. Hat tip to Greg Laden.    

Posted in climate, differential equations, energy, environment, forecasting, geophysics, mathematics, maths, meteorology, NASA, NOAA, oceanography, physics, rationality, reasonableness, science, statistics | Leave a comment

Ray Pierrehumbert on the new U.S.-China climate deal

Professor Pierrehumbert offers his thoughts in Slate. He’s the author of Principles of Planetary Climate which is, as far as I’m concerned, the definitive climate book.

Posted in astronomy, astrophysics, carbon dioxide, carbon dioxide capture, Carbon Tax, chemistry, citizen science, citizenship, civilization, climate, climate education, conservation, consumption, demand-side solutions, differential equations, ecology, economics, education, efficiency, energy, energy reduction, engineering, environment, forecasting, geoengineering, geophysics, investing, investment in wind and solar energy, IPCC, mathematics, maths, meteorology, methane, NCA, NOAA, oceanography, physics, politics, rationality, reasonableness, risk, science, scientific publishing, solar power, statistics, wind power | Tagged | Leave a comment

Brian Hayes on clear climate models for the curious public

American Scientst has a nice article by Brian Hayes recounting the basic physics of climate, and then recommending both public engagement with clear, simple climate models, at least by the curious and scientifically literate, and the development of models which … Continue reading

Posted in astrophysics, carbon dioxide, Carl Sagan, cat1, citizen science, civilization, climate, climate education, conservation, consumption, differential equations, education, energy, environment, forecasting, geophysics, mathematics, maths, meteorology, oceanography, physics, reasonableness, risk, science, scientific publishing, statistics | Leave a comment

Dan Satterfield on Why and How Weather and Climate Models Work

See http://blogs.agu.org/wildwildscience/2014/08/10/weather-climate-models-work-meteorologists-learn-calculus/. 50 minute summary lecture there, by Professor Margot Gerritsen, embedded below, if you really want to know why and how. You, of course, don’t need to know. But, then, don’t criticize climate models, because you’ll be doing it … Continue reading

Posted in climate, climate education, differential equations, environment, forecasting, geophysics, mathematics, maths, meteorology, physics, reasonableness, science, statistics | Leave a comment

Why small effects can make BIG changes. Science rules, as Bill Nye says.

This is why small effects in the climate system can have BIG consequences. Even if the percentage change of CO2 due to human effects as a proportion of total atmospheric mass is very small, the consequences can, be, well, of … Continue reading

Posted in climate, differential equations, education, engineering, environment, geophysics, mathematics, meteorology, physics, rationality, reasonableness, risk, science | Leave a comment

MITx: 12.340x: Global Warming Science | edX

MITx: 12.340x: Global Warming Science | edX. Updated. 31st March 2014. Great interview and Q&A with Professor Professor Christopher Knittel of MIT on “Climate Change Policy that Makes Economic Sense“.

Posted in carbon dioxide, climate, climate education, differential equations, environment, forecasting, geophysics, oceanography, physics, risk, science, WHOI | Leave a comment

“On the Lyapunov function for complex-balanced mass-action systems” Hat tip to the Azimuth Project and thanks to Manoj Gopalkrishnan for this interesting article.

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A trivariate, coupled dynamical system, and hints for using the carbon cycle to explain glacial-interglacial periods

I’m reading K. Soetaert, J. Cash, F. Mazzia, Solving Differential Equations in R. I know Professor Soetaert’s work, from the text co-authored with P. M. J. Herman, A Practical Guide to Ecological Modelling, and the several R packages he has contributed with others. … Continue reading

Posted in climate, climate education, differential equations, ecology, engineering, environment, geophysics, mathematics, maths, meteorology, oceanography, physics, science, Uncategorized | Tagged , , | 4 Comments