Archive for global warming

and it only gets worse…

Posted in Kids, pictures, Travel with tags , , , , , , , , , , on April 7, 2017 by xi'an

The State Department said on Monday it was ending U.S. funding for the United Nations Population Fund, the international body’s agency focused on family planning as well as maternal and child health in more than 150 countries.Reuters, April 3, 2017

“When it comes to science, there are few winners in US President Donald Trump’s first budget proposal. The plan, released on 16 March, calls for double-digit cuts for the Environmental Protection Agency (EPA) and the National Institutes of Health (NIH). It also lays the foundation for a broad shift in the United States’ research priorities, including a retreat from environmental and climate programmes.” Nature, March 16, 2017

“In light of the recent executive order on visas and immigration, we are compelled to speak out in support of our international members. Science benefits from the free expression and exchange of ideas. As the oldest scientific society in the United States, and the world’s largest professional society for statisticians, the ASA has an overarching responsibility to support rigorous and robust science. Our world relies on data and statistical thinking to drive discovery, which thrives from the contributions of a global community of scientists, researchers, and students. A flourishing scientific culture, in turn, benefits our nation’s economic prosperity and security. ​” ASA, March, 2017

and it only gets worse…

Posted in Kids, pictures, Travel with tags , , , , , on March 6, 2017 by xi'an

“Women and children crossing together illegally into the United States could be separated by US authorities under a proposal being considered by the Department of Homeland Security” The Guardian, March 4, 2017

“The Trump administration is expected to begin rolling back stringent federal regulations on vehicle pollution that contributes to global warming (…) essentially marking a U-turn to efforts to force the American auto industry to produce more electric cars. During the same week, Mr. Trump is expected to direct Mr. Pruitt to begin the more lengthy and legally complex process of dismantling the Clean Power Plan, Mr. Obama’s rules to cut planet-warming pollution from coal-fired power plants.” The New York Times, March 5, 2017

“Without offering any evidence or providing the source of his information, Mr. Trump fired off a series of Twitter messages claiming that Mr. Obama “had my ‘wires tapped.’ “ The New York Times, March 5, 2017

simulating Nature

Posted in Books, Statistics with tags , , , , , , , , , , , , , , , on July 25, 2012 by xi'an

This book, Simulating Nature: A Philosophical Study of Computer-Simulation Uncertainties and Their Role in Climate Science and Policy Advice, by Arthur C. Petersen, was sent to me twice by the publisher for reviewing it for CHANCE. As I could not find a nearby “victim” to review the book, I took it with me to Australia and read it by bits and pieces along the trip.

“Models are never perfectly reliable, and we are always faced with ontic uncertainty and epistemic uncertainty, including epistemic uncertainty about ontic uncertainty.” (page 53)

The author, Arthur C. Petersen, was a member of the United Nations’ Intergovernmental Panel on Climate Change (IPCC) and works as chief scientist at the PBL Netherlands Environmental Assessment Agency. He mentions that the first edition of this book, Simulating Nature, has achieved some kind of cult status, while being now out of print,  which is why he wrote this second edition. The book centres on the notion of uncertainty connected with computer simulations in the first part (pages 1-94) and on the same analysis applied to the simulation of climate change, based on the experience of the author, in the second part (pages 95-178). I must warn the reader that, as the second part got too focussed and acronym-filled for my own taste, I did not read it in depth, even though the issues of climate change and of the human role in this change are definitely of interest to me. (Readers of CHANCE must also realise that there is very little connection with Statistics in this book or my review of it!) Note that the final chapter is actually more of a neat summary of the book than a true conclusion, so a reader eager to get an idea about the contents of the book can grasp them through the eight pages of the eighth chapter.

“An example of the latter situation is a zero-dimensional (sic) model that aggregates all surface temperatures into a single zero-dimensional (re-sic) variable of globally averaged surface temperature.” (page 41)

The philosophical questions of interest therein are that a computer simulation of reality is not reproducing reality and that the uncertainty(ies) pertaining to this simulation cannot be assessed in its (their) entirety. (This the inherent meaning of the first quote, epistemic uncertainty relating to our lack of knowledge about the genuine model reproducing Nature or reality…) The author also covers the more practical issue of the interface between scientific reporting and policy making, which reminded me of Christl Donnelly’s talk at the ASC 2012 meeting (about cattle epidemics in England). The book naturally does not bring answers to any of those questions, naturally because a philosophical perspective should consider different sides of the problem, but I find it more interested in typologies and classifications (of types of uncertainties, in crossing those uncertainties with panel attitudes, &tc.) than in the fundamentals of simulation. I am obviously incompetent in the matter, however, as a naïve bystander, it does not seem to me that the book makes any significant progress towards setting epistemological and philosophical foundations for simulation. The part connected with the author’s implication in the IPCC shed more light on the difficulties to operate in committees and panels made of members with heavy political agendas than on the possible assessments of uncertainties within the models adopted by climate scientists…With the same provision as above, the philosophical aspects do not seem very deep: the (obligatory?!) reference to Karl Popper does not bring much to the debate, because what is falsification to simulation? Similarly, Lakatos’ prohibition of “direct[ing] the modus tollens at [the] hard core” (page 40) does not turn into a methodological assessment of simulation praxis.

“I argue that the application of statistical methods is not sufficient for adequately dealing with uncertainty.” (page 18)

“I agree (…) that the theory behind the concepts of random and systematic errors is purely statistical and not related to the locations and other dimensions of uncertainty.” (page 55)

Statistics is mostly absent from the book, apart from the remark that statistical uncertainty (understood as the imprecision induced by a finite amount of data) differs from modelling errors (the model is not reality), which the author considers cannot be handled by statistics (stating that Deborah Mayo‘s theory of statistical error analysis cannot be extended to simulation, see the footnote on page 55). [In other words, this book has no connection with Monte Carlo Statistical Methods! With or without capitals… Except for a mention of `real’ random number generators on—one of many—footnotes on page 35.]  Mention is made of “subjective probabilities” (page 54), presumably meaning a Bayesian perspective. But the distinction between statistical uncertainty and scenario uncertainty which “cannot be adequately described in terms of chances or probabilities” (page 54) misses the Bayesian perspective altogether, as does the following sentence that “specifying a degree of probability or belief [in such uncertainties] is meaningless since the mechanism that leads to the events are not sufficiently known” (page 54).

“Scientists can also give their subjective probability for a claim, representing their estimated chance that the claim is true. Provided that they indicate that their estimate for the probability is subjective, they are then explicitly allowing for the possibility that their probabilistic claim is dependent on expert judgement and may actually turn out to be false.” (page 57)

In conclusion, I fear the book does not bring enough of a conclusion on the philosophical justifications of using a simulation model instead of the actual reality and on the more pragmatic aspects of validating/invalidating a computer model and of correcting its imperfections with regards to data/reality. I am quite conscious that this is an immensely delicate issue and that, were it to be entirely solved, the current level of fight between climate scientists and climatoskeptics would not persist. As illustrated by the “Sound Science debate” (pages 68-70), politicians and policy-makers are very poorly equipped to deal with uncertainty and even less with decision under uncertainty. I however do not buy the (fuzzy and newspeak) concept of “post-normal science” developed in the last part of Chapter 4, where the scientific analysis of a phenomenon is abandoned for decision-making, “not pretend[ing] to be either value-free or ethically neutral” (page 75).

Le Monde rank test

Posted in R, Statistics with tags , , , , , , , , on April 5, 2010 by xi'an

In the puzzle found in Le Monde of this weekend, the mathematical object behind the silly story is defined as a pseudo-Spearman rank correlation test statistic,

\mathfrak{M}_n = \sum_{i=1}^n |r^x_i-r^y_i|\,,

where the difference between the ranks of the paired random variables x_i and y_i is in absolute value instead of being squared as in the Spearman rank test statistic. I don’t know whether or not this measure of distance has been studied in the statistics literature (although I’d be surprised has it not been studied!). Here is an histogram of the distribution of the new statistics for n=20 under the null hypothesis that both samples are uncorrelated (i.e. that the sequence of ranks is a random permutation). Each point in the sample was obtained by

perm=sample(1:20)
saple[t]=sum(abs(perm[1:10]-perm[11:20]))

When regressing the mean of this statistic \mathfrak{M}_n against the covariates n and n^2, I obtain the uninspiring formula

\mathbb{E} [\mathfrak{M}_n] \approx 0.1681 n^2 - 0.3769 n + 11.1921

which does not translate into a nice polynomial in n!

Another interesting probabilistic/combinatorial problem issued from an earlier Le Monde puzzle: given an urn with n white balls and n black balls that is sampled without replacement, what is the probability that there exists a sequence of length 2k with the same number of white and black balls for k=1,\ldots,n? If k=1,n, the answer is obviously one (1), but for some values of k, it is less than one. When n goes to infinity, this is somehow related to the probability that a Brownian bridge crosses the axis in-between 0 and 1 but I have no clue whether this helps or not! Robin Ryder solved the question for the values n=50 and k=24,25 by establishing that the probability is still one.

Ps- The same math tribune in Le Monde coincidently advertises a book, Le Mythe Climatique, by Benoît Rittaud that adresses … climate change issues and the “statistical mistakes made by climatologists”. The interesting point (if any) is that Benoît Rittaud is a “mathematician not a statistician”, with a few papers in ergodic theory, but this advocated climatoskeptic nonetheless criticises the use of both statistical and simulation tools in climate modeling. (“Simulation has only been around for a few dozen years, a very short span in the history of sciences. The climate debate may be an opportunity to reassess the role of simulation in the scientific process.”)

Climatic street fight

Posted in Books, University life with tags , , on April 3, 2010 by xi'an

While a former US vice-president, Al Gore, dedicates his time and energy to warn about global warming, a former French minister for education and retired head of the Earth sciences institute in Paris (IPGP) engages into a crusade against it! Claude Allègre is an internationally recognised geochemist and a member of the French Academy of Sciences, as well as a foreign correspondent of the US National Academy of Sciences, but his attempts at establishing that climate change is part of a natural cycle and not partly induced by human activities are of a very low scientific level. He recently published a popular science book called L‘Imposture Climatique ou la Fausse Ecologie where he repeatedly bends facts and references to fit his thesis. (The curve above is a reproduction of the curve of temperatures shown in the book [black] versus the one initially published by Grudd [in red].) The impact of this book is obviously negligible at the scientific level, but the agressivity of Allègre’s tone against academic climate specialists is such that a petition of 400 scientists protesting against the accusations contained in the book (and reflecting the current suspicions from the “public” about climatologists) has been sent to the current minister for higher education and research, as well as to the Academy of Sciences, in order to establish the debate at the proper academic level. Not that this should have the slighest impact on public opinion, of course! (Or it could simply reinforce the lack of trust about “scientific” arguments…)