Category Archives: Lorenz

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

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 walk in a parameter space. … 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 | Leave a comment

“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 | Leave a comment

“Stochastic Parameterization: Towards a new view of weather and climate models”

Judith Berner, Ulrich Achatz, Lauriane Batté, Lisa Bengtsson, Alvaro De La Cámara, Hannah M. Christensen, Matteo Colangeli, Danielle R. B. Coleman, Daan Crommelin, Stamen I. Dolaptchiev, Christian L.E. Franzke, Petra Friederichs, Peter Imkeller, Heikki Järvinen, Stephan Juricke, Vassili Kitsios, François … Continue reading

Posted in biology, climate models, complex systems, convergent cross-mapping, data science, dynamical systems, ecology, Ethan Deyle, Floris Takens, George Sughihara, Hao Ye, likelihood-free, Lorenz, mathematics, meteorological models, model-free forecasting, physics, population biology, population dynamics, quantitative biology, quantitative ecology, Scripps Institution of Oceanography, state-space models, statistical dependence, statistics, stochastic algorithms, stochastic search, stochastics, Takens embedding theorem, time series, Victor Brovkin | 4 Comments

All I do is complain, complain …

I was reviewing a presentation given as part of a short course in the machine learning genre today, and happened across the following two bullets, under the heading “Strictly Stationary Processes”: Predicting a time series is possible if and only … Continue reading

Posted in bifurcations, chaos, citizen science, convergent cross-mapping, dynamic linear models, dynamical systems, engineering, Floris Takens, generalized linear models, geophysics, George Sughihara, ignorance, Lenny Smith, Lorenz, mathematics, maths, meteorology, prediction, probability, rationality, reasonableness, statistics, stochastic algorithms, stochastic search, stochastics, Takens embedding theorem, the right to know, time series | 1 Comment