## Yea, BOSTON!

MAKING CLIMATE CHANGE DATA ACCESSIBLE

Today, the City of Boston released ClimateChangeData.Boston.gov. The City website features scrubbed information from the U.S. EPA Climate Change website.

Just another band out of Boston …

## Causation and the Tenuous Relevance of Philosophy to Modern Science

I was asked by ATTP at their blog:

hypergeometric,
Which bit of what Dikran said do you disagree with? It certainly seems reasonable to me; if you want to explain how something could cause something else, you need to use more than just statistics.

After consideration, I posted a long explanation, worthy of a blog post on its own. But I’m leaving it there, and just putting a link to it here.

## Deloitte: The drumbeats for the extinction of utilities have begun

From The Economist, 25th February 2017:

FROM his office window, Philipp Schröder points out over the Bavarian countryside and issues a Bond villain’s laugh: “In front of you, you can see the death of the conventional utility, all financed by Mr and Mrs Schmidt. It’s a beautiful sight.”

Microgrids where the Big Grids don’t go.

Why microgrids.

## Statements by the Ecological Society of America on the proposed U.S. exit from the Paris Agreement, and on Climate Change

By withdrawing from the Paris Agreement on climate change, the United States is abdicating its role as the world leader in using science-based information to inform policy. Business, political, and scientific leaders the world over are condemning the decision. More than 190 signatory nations agreed to take actions towards reducing future temperature increases and addressing the serious threats posed by a changing climate to people, livelihoods, and nature. The science-based evidence is clear that humans are driving climate change.

Management strategies have traditionally operated under the assumption that natural systems fluctuate within a certain range—the past has served as an indicator of future conditions. But this assumption does not hold in the face of rapid climate change. Even conservative warming projections show that natural systems will experience unprecedented stresses, including shifting habitats and ecological processes (e.g. wildlife migration and reproduction) and more frequent and severe natural disturbances, such as fires, floods, and droughts. These unavoidable changes will require management that addresses ecological thresholds, tipping points, and other sources of uncertainty. Ecosystems are naturally dynamic and diverse—they are the products of change and adaptation. But human activity has impaired the ability of many systems to respond. Preserving natural function is central to maintaining resilience and safeguarding ecosystem services in the face of climate change.

I am a member of the Ecological Society of America (ESA). Great technical literature! Interesting problems!

## Installed Non-Utility Solar, Massachusetts, 12/2016

(Click on image to see a larger figure, and use browser Back Button to return to blog.)

## Prayer Vigil for the Earth, Needham Common, Massachusetts, 4 June 2017

Led by our own UU Needham Reverand Catie Scudera, with Reverand Daryn Bunce Stylianopoulos of the First Baptist Church of Needham, and Reverend Jim Mitulski of the Congregational Church of Needham, Sunday, 4th June 2017 saw a vigil of members of their combined congregations, singing songs of reflection and protest in response to Thursday’s announcement by President 45, that he would withdraw the United States from the Paris Climate agreement.

In response …

Why? Oh, why not try something from an episode on Tyson’s excellent Cosmos:

(properly, for pay) https://www.amazon.com/The-Lost-Worlds-Planet-Earth/dp/B00K5M962G

And, for background to this, read Ogden and Sleep.

In the world in excess of $+2\textdegree$, dragons prowl. The most obvious are methane clathrates, but who knows what else.

And, while solemn, the songs, the sun, and the moment were memorable.

And there is some good news, even if it is partial.

## Disney’s Robert Iger resigns from Trump advisory panel over the Trumpistas’ decision to quit COP

“Protecting our planet and driving economic growth are critical to our future, and they aren’t mutually exclusive,” he said in a statement. “I deeply disagree with the decision to withdraw from the Paris Agreement and, as a matter of principle, I’ve resigned from the President’s advisory council.”

— Disney’s CEO, Robert Iger

Story from Variety.

## GForce Waste Sorters!

Check out their Wide World of Waste.

## Exxon Shareholders Approve Climate Resolution: 62% Vote for Disclosure’

Flash from InsideClimate News:

ExxonMobil shareholders voted Wednesday to require the world’s largest oil and gas company to report on the impacts of climate change to its business—defying management, and marking a milestone in a 28-year effort by activist investors.

Sixty-two percent of shareholders voted for Exxon to begin producing an annual report that explains how the company will be affected by global efforts to reduce greenhouse gas emissions under the Paris climate agreement. The analysis should address the financial risks the company faces as nations slash fossil fuel use in an effort to prevent worldwide temperatures from rising more than 2 degrees Celsius.
.
.
.
… [I]nstitutional investors argue that climate risk is a long-term financial risk that should be integrated into financial reporting.

BlackRock, the world’s largest investment firm, with $5.1 trillion in assets under management, and several major global investors—including State Street, Aviva, and Legal & General—have signaled that they want more transparency on climate change risk. BlackRock’s first vote against corporate management on climate came this year against Occidental, where it was the largest institutional investor. . . . Patrick Doherty, director of corporate governance for the New York State Office of the State Comptroller, which spearheaded the Exxon resolution along with the Church of England, said that climate is a very real financial concern for the employees paying into state pension funds and looking to payouts decades into the future. The New York State Common Retirement Fund, one of the world’s largest public employees investment funds, holds more than$1 billion in Exxon stock.

“We have a very, very strong financial interest in the long-term health of the company,” Doherty said.

“The average CEO has a tenure of five years, and hedge funds are looking to maybe the next quarter,” he said. “Only institutional investors have this longer view. And one of the reasons that support for climate disclosure has been increasing over the years is more and more institutional shareholders are saying, hey, there can be large long-term risk and long-term damage.”

(The above is the Carbon Tracker 2014 Unburnable Carbon report.)

And regarding the claim that

Oil companies cannot predict the long-term impact of climate and climate policy with enough precision to provide the kind of risk analysis that shareholders are seeking, IHS Markit said. Financial disclosure under securities regulation looks ahead over a much shorter time frame.

what Markit is saying is that the management of fossil fuel companies does not know how to do their job. If that is correct, which I doubt, they should step aside and allow someone who knows how to do it, do it.

## Dikran Marsupial’s excellent bit on hypothesis testing applied to climate, or how it should be applied, if at all

Frankly, I wish some geophysicists and climate scientists wrote more as if they thoroughly understood this, let alone deniers to try to discredit climate disruption. See “What does statistically significant actually mean?”.

Of course, while statistical power of a test is important to keep in mind, as well as the effects of arbitrary alterations or recodings of data upon it (see also Andrew Gelman’s comment on this), people should really look at this from a purely Bayesian perspective, and there’s no longer a computational excuse to ignore that approach.

## The Rule of 135

From SingingBanana.

## Massachusetts Senate, Climate and Clean Energy Tour (Senator Marc Pacheco, and others), testimony

I testified at the Weymouth, Massachusetts hearing for the MA Senate Climate and Clean Energy Tour.

Here’s Senator Marc R Pacheco introducing the Tour:

The Weymouth hearing was recorded and is available on YouTube in three parts:

My written testimony is attached below:
20170524TestimonyToCleanEnergyTour-Weymouth–JGalkowski20170522

## “Bigger Isn’t Always Better When It Comes to Data”: Barry Nussbaum

The President’s Corner in the May 2017 issue of Amstat News, the monthly newsletter of the American Statistical Association (“ASA”), features the interesting exposition by environmental statistician and President of the ASA, Barry Nussbaum, called “Bigger isn’t always better when it comes to data.” Key paragraph:

Notice a subtle nuance here. Normally, you have a population and you sample elements from the population. Here, we really didn’t know if the vehicle’s emissions belonged to the population, due to the maintenance and use restrictions, until we administered the questionnaire after the vehicle had been randomly selected.

## Akamai Technologies invests in Texas wind farm

Akamai (NASDAQ: AKAM) said it is making a 20-year investment in the planned Seymour Hills Wind Farm, which will be based outside of Dallas and is expected to begin operating next year. The project is being developed by Infinity Renewables, and the plan is to construct 38 wind turbines across about 8,000 acres, Akamai said in a news release. Akamai said it intends to pull enough energy from the wind farm to offset its aggregate data center operations based in Texas, which account for about 7 percent of Akamai’s global power load.

This is part of Akamai’s commitment to reduce Carbon emissions and cover 50% of its operating requirements for electrical energy by 2020. See the details in Akamai’s press release.

## “The [transport-as-a-service] disruption will crater the value chain of the oil industry” (RethinkX)

… By 2030, the report predicts that oil demand will drop to 70 million barrels per day. The resulting collapse in prices will be catastrophic for the industry, and these effects are likely to be felt as early as 2021.

The report suggests that oil demand from passenger road transport will drop by 90 percent by 2030; demand from the trucking industry will drop by 7 million barrels per day globally. This is, as the report says, an existential crisis for the industry. Current share prices and projections are based on the presumption of a system of individually owned vehicles.

See the news report for an overview, and the detailed report written by James Arbib and Tony Seba of RethinkX.

As far as I’m concerned, it couldn’t happen to a “nicer” bunch of people, this economic catastrophe. And it can’t happen soon enough!

## Evidence of a decline in electricity use by U.S. households’ (Prof Lucas Davis, U.C. Berkeley)

This is from a blog post by Professor Lucas Davis at his blog. In addition to the subject, that’s an interesting way of presenting a change over time I’ll need to think about: It seems the model could be used in other, more comprehensive ways. Note it’s really a matched pairs test, where each state is a candidate and its electricity use in 2010 is match with that in 2015. Even though the amount of electricity used by any individual state over time is a dependent quantity, electricity use of one state is more or less independent of that in another state. They might be dependent if, say, the United States economy crashed, or if it underwent a sudden boom.

## I’m afraid, dear progressive friends, Mr Maher is 110% correct

I see nearly every week in the comedy called progressive plans for energy sources in the Commonwealth of Massachusetts. Progressives, it seems, eschew cooperation with business and attorneys and, as a result, never get anything respectable done. They are, as I’ve sometimes remarked, in practice, liberal climate deniers, because they rate the survival of their collective political power more important than that of civilization.

(Hat tip to Climate Denial Crock of the Week)

## Investing, and Sharpe’s inequality

Posted in investments, statistics | 2 Comments

## Liang, information flows, causation, and convergent cross-mapping

Someone recommended the work of Liang recently in connection with causation and attribution studies, and their application to CO2 and climate change. Liang’s work is related to information flows and transfer entropies. As far as I know, the definitive work on that is James, Barnett, and Crutchfield, “Information Flows? A Critique of Transfer Entropies.” The former paper claims, in part,

The whole new formalism is derived from first principles, rather than as an empirically defined ansatz, with the property of causality guaranteed in proven theorems. This is in contrast to other causality analyses, say that based on Granger causality or convergent cross mapping (CCM)

Well I’ve written about CCM here before, in 2013, 2016, and just recently.

Anyway, I don’t see anything obviously superior regarding Liang’s information flows approach, at least in comparison with Granger causality or CCM, and, so, I’ll take conclusions about causation of CO2 and climate they derive with a big grain of salt. I prefer Egbert van Nes, Marten Scheer, Victor Brovkin, Timothy Lenton, Hao Ye, Ethan Deyle, and George Sugihara on “Causal feedbacks in climate change.”

## Just because the data lies some times doesn’t mean it’s okay to censor it

Or, there’s no such thing as an outlier …

Eli put up a post titled “The Data Lies. The Crisis in Observational Science and the Virtue of Strong Theory” at his lagomorph blog. Think of it: Data lying. Obviously this is worth a remark. After all, the Bayesian project is all above treating data as given and fixed, a nod of deep respect, and then, in a kind of generalization of maximum likelihood philosophy, finding those parameters offered by theory which are most consistent with it. But in experimental and, especially, observational science things aren’t so easy.

So I say … Maybe it is …

Well. Of course. Eddington: “It is also a good rule not to put overmuch confidence in the observational results that are put forward until they are confirmed by theory” (from his book). On the other hand …

It is also possible to score theory’s consistency with experiment with techniques better than t-tests and the like, notably the important information criteria that have been developed (Burnham and Anderson). These are bidirectional. For example, it is entirely possible an observational experiment, however well constructed, might be useless for testing a model. Observational experiments are not as powerful in this regard as are constructed experiments.

But I think the put-down of the random walk as a model is a bit strong. After all, that is the basis of a Kalman filter-smoother, at least in the step-level change version. Sure, the state equation need not assume random variation and could have a deterministic core about which there is random variation. But it is possible to posit a “null model” if you will which involves no more than a random walk to initialize, and then takes advantage of Markov chains as universal models to lock onto and track whatever a phenomenon is.

Better, it’s possible to integrate over parameters, as was done in the bivariate response for temperature anomalies in the above, to estimate best fits for process variance. It’s possible to use priors on these parameters, but the outcomes can be sensitive to initializations. It’s also possible to use non-parametric smoothing splines fit using generalized cross-validation. These are a lot better than some of the multiple sets of linear fits I’ve seen done in Nature Climate Change and they tell the same story:

No doubt, there are serious questions about how pertinent these models are to paleoclimate calculations. However, if they are parameterized correctly, especially in the manner of hierarchical Bayesian models, these could well provide constraints in the way of priors for processes which could be applicable to paleoclimate.

While certainly theory can be used, and much of it is approachable and very accessible, I understand why people might want to do something else. Business and economic forecasts are often done using ARIMA models, even if these are not appropriate.

But there is an important area of quantitative research which offers so-called model-free techniques for understanding complex systems, and, in my opinion, these should not be casually dismissed. In particular, the best quantitative evidence of which I am aware teasing out the causal role CO2 has for forcing at all periods comes from this work. In fact, I’m surprised more people aren’t aware of — and use — the methods Ye, Deyle, Sugihara, and the rest of their team offer.

I should mention, too, that there are R packages called:

• Package nwfscNLTS: Non-linear time series
• Package rEDM: an R package for Empirical Dynamic Modeling and Convergent Cross-Mapping
• Package multispatialCCM: Multispatial Convergent Cross Mapping

[P.S. Sorry, I can’t help it if Judith Curry likes it, too. It’s good stuff.]

But, personally, I like Bayesian Dirichlet stick-breaking …

## A response to “We might not be certain but …” at … and Then There’s Physics

I posted a response to a comment from the blog author at the ellipsis-loving … and Then There’s Physics. The figures didn’t make it into the comment, and, so, I am reproducing the intended comment in its entirety here.

ATTP, you were correctly pointing out I was partly incorrect, and certainly incomplete. Kudos to you, and apologies, and to the readers.

I hadn’t read Armour 2017. I have now. I did read ATTP’s assessment and, yes, it does mention Armour deals with nonlinearity. And, yes, it does mention that the histogram is from CMIP runs, but I interpreted it differently than it should have been interpreted. I have not read Richardson, and probably won’t. I also assumed that the Armour figure was something Stephens was using in his “criticism of excessive certainty” but have gone back and seen that there is another parse to this post which is consistent with Stephens not mentioning Armour at all.

I also have not read Stephens, and perhaps I should before commenting, but I won’t.

The point I tried to make was essentially that uncertainty and ignorance in a place where a decision ought to be made and when the consequences could be enormous is not the place to claim “It’s okay to remain ignorant.” Essentially, this is enshrining the “Do nothing until someone proves you have to do so” which might work for some common decisions, but taking a big ship into an iceberg-strewn sea because it hasn’t hit anything yet hardly seems prudent.

I also am not convinced, commenting with respect for Armour, that the adjustment for nonlinearity they attempt helps the argument much, and ATTP hinted at that in his previous post (beginning “… A few additional points. We don’t know that these adjustments are correct. However, we do have a situation where there is a mismatch between different climate sensitivity estimates …”). In the public discussion of climate change, highlighting these kinds of papers tends, I think, to convince people there’s more arbitrariness to this process than is correct. After all, there have been similar papers published by Meraner, Mauritsen, and Voigt, as well as Caballero and Huber, the latter focussing upon nonlinearity in ECS and having a good introduction. These emphasize Pierrehumbert’s comment “Here there (may) be dragons”, and, as of 2013,

…there have already been great strides in understanding the magnitude and pattern of warmth in hothouse climates, which have helped resolve some earlier modeling paradoxes, but much remains to be done. In particular, narrowing the broad error bars on past atmospheric CO2 is crucial to relating these climates to what is going on at present.

More recently there is the published work of Friedrich, Timmermann, Tigchelaar, Timm, and Ganopolski.

Consider Pierrehumbert’s equation (3.14) for temperature sensitivity (specifically mean surface temperature) with respect to some parameter, $\Lambda$, where $\Lambda$ might be, as Pierrehumbert suggests, albedo, or CO2 concentration, or the solar constant:

$\frac{dT}{d\Lambda} = -\frac{\frac{\partial{}G}{\partial{}\Lambda}}{\frac{\partial{}G}{\partial{}T}}$

Here $G$ is the top-of-atmosphere flux, and $\text{OLR}$ is outgoing longwave radiation at the surface (*). This is pretty standard, even if it is very general, much more general than, say, Armour’s equations (1)-(3). From a statistical perspective what’s striking about the above is that if

$\frac{\partial{}G}{\partial{}\Lambda}$

and

$\frac{\partial{}G}{\partial{}T}$

are each interpreted to be random variables worthy of estimation by whatever means, then that implies $\frac{dT}{d\Lambda}$ is a random variable which is drawn from a ratio distribution. And should the Highest Density Probability Interval for $\frac{\partial{}G}{\partial{}T}$ include zero, whatever the physical reason, the distribution of $\frac{dT}{d\Lambda}$ is pretty meaningless. A good physical imagination offers any number of ways this could happen, but Professor Pierrehumbert’s discussions in Section 3.4 of his book describes the possible (mathematical) range, irrespective of the geophysical details. And because what we are about is $\delta{}T$ as a function of all relevant $\Lambda$, that being a total differential, the excessive variability in any one such $\Lambda$ will dominate that of the rest. Note extreme variability is not our friend, no matter what vision of a cultural or economic future we might have.

If ECS is going to continue to be used as the basis of argument and policy, it seems to need to be made far more robust than it is. That’s the point of my argument for much more additional work. If we are to keep this troubled concept in the planning stables, we desperately need to understand the bounds on its applicability. Armour is a start, but Armour simply says there might be problems when we already know there are problems from theory. What we need are constraints. Otherwise, ECS is a “nice to have if the world were a different place.” But then we don’t really have it, except knowing that there could be “dragons” out there.

I think there are much better arguments, and there are much better problems to chase. For instance, here is the definitive plot from Fyfe, Gillett, and Zwiers:

I have noted (**; Section 7) that what’s wrong with this presentation is not that that the Highest Density Probability Interval for the climate models fails to overlap the observational mean and cloud, it’s that there is such a big difference between the observational variance and that of the model ensemble. The specifics of the discrepancy seen as a t-test based upon a difference in means led to the later explanation by Cowtan and Way and then a rebuttal by Fyfe and Gillett. I say, rather, that the reason for the discrepancy is deep, having to do more with the difference in variances (***), and probably not something we can expect most public or most policymakers to understand, at least without understanding something like Leonard Smith’s Chaos: A Very Short Introduction. The climate ensemble simulates all possible futures, and Earth takes one future at a time. I have read all around this in the literature, and there seems to be a confusion about what internal variability means. Yes, there’s unexplained internal variability, but there’s a lot of evidence for stochastic variability even if all the phenomena in internal variability were deeply understood. That’s important, because it makes what Bret Stephens and others like Judith Curry want to do a fundamentally flawed project. This stochastic variability on top of everything could be enough to send us all over some kind of potential cliff, even if emissions were managed to some precalculated minimax loss-versus-economic benefit point.

Here’s a rhetorical question when dealing with the public and policymakers: Why not go back to simple conservation of energy arguments, and point out that radiative forcing from CO2 is indisputable? The excess energy from forcing is going to go somewhere, and where it’s gone in the past may not be where it continues to go, ditto CO2 itself. Sure, this frustrates people who want a cost put on the phenomenon. But making up a cost is arguably worse than saying “We don’t have one.” Will the latter produce inaction? Possibly. But that’s what’s happening now, and people are trying to produce cost estimates.

Oh, and indeed, there are but 21 single socks in the Broman climate collection, per Armour’s count of the number of GCMs used reported at the top right of the second page of their article.

Other work on climate sensitivity is reported by Held and Winton (assuming the NOAA site continues to be maintained), and at Isaac Held’s blog.

(*) See Professor Ray Pierrehumbert’s book for the intimate portrait of Earth as a planet, in the manner of Arnold Ross, with associated and very fine Python code.

(**) WARNING: Not peer-reviewed.

(***) Were the observational variance to be appreciably larger, the conclusion of a statistical test would be that the difference in means was less significant.

## Why we sold our Disney Vacation Club timeshares

Hat tip to Climate Denial Crock of the Week, in their “Florida slowly confronting sea level nightmare.”

## March for Science, Boston, 22 April 2017

Cold and wet. A very typical Massachusetts day in Spring.

But great …

## “You don’t have that option.”

Dr Neil deGrasse Tyson. I think he’s awesome. Marvelous. I saw him in Boston. He and I did not get off well, at the start, because of my being awestruck, and feeling very awkward, and the short time we had in his meeting us backstage in Boston. I regret that, but I could not be other than what I was.

But he is someone I will and do always admire, and follow. He knows how to challenge and communicate.

He’s great.

And he would be the first to challenge that.

Because of Science. And its values. “Prove it,” I think he’d say.

This is much better than Religion, although those are my feelings and thoughts, not Dr Tyson’s.

“This is Science. It’s not something to toy with.”

All this is about people, and the human situation. Science is a means of getting beyond that.

“Recognize what Science is, and allow it to be and what it can be in the service of civilization.”

March for Science, Saturday, 22nd April 2017. Earth Day. I will be marching in Boston. And I will be doing it as a member of:

And, I believe, citizen scientists have a big role to play in the Science of now and of the future. And, yes, that’s a very real thing.

Update, 2017-04-21

It seems fitting to have another image of the Pale Blue Dot here, taken by JPL’s Cassini at Saturn, on 12th April 2017.

## “Hadoop is NOT ‘Big Data’ is NOT Analytics”

Arun Krishnan, CEO & Founder at $\mathbf{n!}\,$ Analytical Sciences comments on this serious problem with the field. Short excerpt:

… A person who is able to write code using Hadoop and the associated frameworks is not necessarily someone who can understand the underlying patterns in that data and come up with actionable insights. That is what a data scientist is supposed to do. Again, data scientists might not be able to write the code to convert “Big Data” into “actionable” data. That’s what a Hadoop practitioner does. These are very distinct job descriptions.

While the term analytics has become a catch-all phrase used across the entire value chain, I personally prefer to use it more for the job of actually working with the data to get analytical insights. That separates out upstream and downstream elements of the entire data mining workflow.

I have repeatedly observed practitioners and especially managers who treat — or would very much like to treat — tools and techniques from this area as if they were Magical Boxes, to which you can send arbitrary data and obtain wonderful results, like the elixir of the Alchemists. There is also a cynical aspect to the attitude of some managers — some seem indoctrinated by the old “Internet time“ and “agile sprint” notions — that if something does not show tangible and substantial progress over the short term (on the order of a week or two), there is something fundamentally wrong with the process. Sure, progress needs to be shown and reportable, but some problems, especially those involving data which are not obviously meaningful (*), demand a deep familiarization with the data and good deal of data cleansing (**). This is hard, especially when the data are large. And not all worthwhile problems can be solved in two weeks, even for a corporation. Consider the project and planning timelines which a Walt Disney Company does for their parks or a energy company like DONG does for their offshore wind projects.

This is unfortunate, and it is more than simply a matter of personal style. Projects which proceed with the magical thinking that the right tool or algorithm is going to solve all their issues typically fail, after expending large resources on computing assets, data licenses, and labor. When they do, they give analytics and “Big Data” a tarnished reputation, especially among upper management who blame and distrust new things rather than incompetent engineers or, perhaps, engineers without the integrity of explaining to their management that these tools have promise, but the project schedules for venturing into new sources of data are long, and best done with a very small team for the first portion.

In fact, one severe failing of the current suite of “Big Data” tools I see is that, while they are strong on certain modeling algorithms, and representational devices like Python panadas-esque and R-esque data frames, they offer little in the way of advanced data cleaning tools, ones which can marshall clusters to completely rewrite data in order for it to be useful for analysis and machine learning.

(*) Data which are obviously meaningful consist of self-evident records like purchasing transactions, or, as is increasingly less common, have records and fields documented carefully in a data dictionary. These have fallen out of fashion because of the NoSQL movement and I applaud the desire to push analysis and data sources beyond structured data offerings. However, just because an analytical can parse unstructured text does not mean it somehow automatically recovers meaning from that text. Indeed, what you have now, instead of structured data, is a problem in natural language processing, for which there are, indeed, excellent tools available, like Python’s nltk. But few people who embrace NoSQL know or use this kind of thing.

It is even harder to know what to do with semi-structured textual data, such as the headers of IETF RFC 2616. In these cases, while there is official guidance, there is no effective enforcement mechanism and, so, instances of these headers are, by the criteria of the RFC, malformed, even if there dialects in Internet communities which are self-consistent and practiced in breach of the RFC. The trouble is that, here, there is no computable definition of malformed, so what is meaningful is something which needs to be learned from the corpora available. This is not an easy task, and may be dependent not only upon the communities in question, but upon geographic origins and takeup, as well as Internet protocol and netblocks.

(**) There are plenty of examples of these in the single thread, single core world. There is, for instance, an open source version called OpenRefine.

## Global blinding, or Nature’s revenge against meteorologists who deny climate disruption

Given climate disruption due to radiative forcing from excess atmospheric CO2, which is a premise of this blog, it is only reasonable to wonder about, speculate, hypothesize, and posit that eventually the amount of this forcing and the feedbacks in terms of latent water vapor, latent heat, and excess energy in atmosphere begin to change the rules which both meteorological education and meteorological forecasting experience have learned over time. Whenever this occurs, and it seems it eventually must, forecasting skill of meteorologists will deteriorate, and this deterioration should be detectable.

I call this, for want of a better term, global blinding, and, whatever it is called, it will have consequences. These will be in preparedness for extreme events, for crop forecasts, for extended supply chains, and for retail markets, as well as for day-ahead forecasts for renewable energy. Until now, this has been a reasonable proposition and suspicion, albeit backed by Physics.

But today, the Bulletin of the American Meteorological Association published a paper by Professor Kerry Emanuel of MIT titled “Will global warming make hurricane forecasting more difficult?” which documents, at least to my knowledge, the first instance of this global blinding, the inability to forecast at what might be the most important moment, at landfall, the onslaught a hurricane poses for a coast, due to global climate change and the radiative forcing to which I refer. Professor Emanuel is one of if not the worldwide expert on tropical storms.

This is deliciously ironic, for there is a small population of meteorologists who have made it their standard practice to deny climate disruption and humanity’s part in it. Unfortunately, there is a much larger population of meteorologists who understand the science, and whose skills are being also obsolesced by Nature, or, rather, what we are doing to its climate in our collective, and completely foolhardy experiment to see if we can survive burning all the the fossil fuels reasonably available on Earth.

But, to me, it entirely makes sense. Given the collective paleoclimatological evidence from the Paleogene, and a little knowledge of nonlinear dynamical systems, it seems strange to think that anyone who understands these matters would think their heuristics and experience would continue to apply in a world which is no longer as stable as it once was.

## The 1793 Fugitive Slave Act and Sanctuary Cities for Slaves in the United States

Interesting piece, from WBUR’s Cognescenti, about the town of Lowell, MA choosing to be a sanctuary city for slaves — in defiance of a standing federal law. That was followed in 1850 by the Fugitive Slave Law, which subjected state and local officials a then onerous \$1,000 fine for failing to return a fugitive slave, and private citizens who aided fugitive slaves were potentially subject to 6 months in prison. Note how Massachusetts responded:

In 1855, in defiance of an updated federal Fugitive Slave Act that heavily favored slave holders, the Massachusetts state Legislature passed the Personal Liberty Act that guaranteed runaways various protections, including the right to a jury trial. The Act also made it difficult — and costly — for slave owners to prove their case in court. The slave-owning South was incensed.

Even if this and other laws like it were eventually ruled unconstitutional (in Priggs v. Pennsylvania), these were practices of civil disobedience mounted at the state and city level.

There is informal discussion available advocating that there is a legal category of being a citizen of a state in the United States but not of the United States federal government. See also. I do not know the legal depth, if any, of these arguments. I do know that certain states, including Massachusetts, have home rule provisions, but I do not think these have anything to do with their relationship to the central government.

(Please note that I am not an attorney and nothing written here should be taken as any kind of legal advice or counsel.)

See also a related article in Portside, and at The Atlantic. Note also articles from William Lloyd Garrison’s The Liberator.

Reverend Theodore Parker was charged with inciting an abolitionist riot in defiance of federal law. Reverend Parker wrote to President Millard Fillmore:

There hangs in my study … the gun my grandfather fought with at the battle of Lexington… and also the musket he captured from a British soldier on that day. If I would not peril my property, my liberty, nay my life to keep my parishioners out of slavery, then I should throw away these trophies, and should think I was the son of some coward and not a brave man’s child.

Reverend Parker was acquitted.

There’s also this, from the Constitution of the Commonwealth of Massachusetts:

IV.–The people of this Commonwealth have the sole and exclusive right of governing themselves as a free, sovereign, and independent state; and do, and forever hereafter shall, exercise and enjoy every power, jurisdiction, and right, which is not, or may not hereafter, be by them expressly delegated to the United States of America, in Congress assembled.

I added some emphasis there, but that’s pretty in-your-face to the federal government.

VII.–Government is instituted for the common good; for the protection, safety, prosperity and happiness of the people; and not for the profit, honor, or private interest of any one man, family, or class of men; Therefore the people alone have an incontestible, unalienable, and indefeasible right to institute government; and to reform, alter, or totally change the same, when their protection, safety, prosperity and happiness require it.

XXIV.–Laws made to punish for actions done before the existence of such laws, and which have not been declared crimes by preceding laws, are unjust, oppressive, and inconsistent with the fundamental principles of a free government.

XXV.–No subject ought, in any case, or in any time, to be declared guilty of treason or felony by the legislature.

Of course that Constitution has a lot of odd parts, at least by today’s standards, e.g., Articles I, II, and III of selfsame Declaration of Rights of Inhabitants of the Commonwealth, but note this part of Chapter I, Section II, Article II:

… And to remove all doubts concerning the meaning of the word “inhabitant” in this constitution, every person shall be considered as an inhabitant, for the purpose of electing and being elected into any office, or place within this State, in that town, district, or plantation, where he dwelleth, or hath his home.

## Taking advantage of the natural skepticism and integrity of scientists and their co-workers, and their commitment to scientific process

I’ve seen this. One can seldom discuss or debate a science denier, whether at (my) presentations at UUAC Sherborn or in many places online, without their employing moving the goalposts or, when they fail to response to an explanation, trotting out another objection. They also do it only in very public fora, whether major media outlets, like the New York Times or the Washington Post or on Ars Technica, not well known publicly, but where many skilled people in computing and information technology hang out. They never do it here, at my blog, possibly because of my track record in dealing with comments like that, and possibly because I just don’t get the traffic.

I think the same is true of publications in peer-reviewed science, touching upon climate. Groups are funded to advance various climate zombies in new guises, and this depletes and distracts efforts by climate scientists and their students who need to respond. It’s very interesting when, if one can, follow the funding sources for these efforts. The publications are seldom in major journals.

Of course now, with the new anti-scholar administration, the attack on funding sources is direct. I’m sure that not only will divisions and organizations having to do with Earth-based sciences within agencies be shut down, but grants for science pertaining to these fields will be forcibly cut.

But I never thought it would be otherwise,, and that’s why in part I have been so focussed on doing what’s needed.

Of course, now it’s necessary to turn attention, once more, away from the activities which are not likely to pay off in the near future, and back to doing sound science, despite what the Champions of Ignorance decide and achieve. I don’t need a grant to do what I do. I am not beholden to anyone for tenure. I work for industry, and they like me.

In your ear, West Wing, Pruitt, and Perry.

Sure, it’s their fault, primarily. But, too, I continue to blame each and every American who voted for them, and their pathological addiction to magical thinking. Quoting Dr Stenger from there:

You cannot use scare tactics with people, who won’t listen. Americans are narcissistic; to make changes, they have to see the advantages individually.

And I quote my personal assessment:

… Individualism in the United States has … triumphed over most other cultural values, at least since the 1980s. The icon of modern individualism is the so-called “smart phone”, and the iconic smart phone is the chic, sleek iPhone. It has extended to the point that some Americans feel if they cannot understand something technical immediately, it is the explainer’s fault or the fault of the material, and, so, they should not invest the effort trying to understand it. I personally trace this idea to a form of “magical thinking” where, since the theology of the Great Awakenings, “all that matters” is the relationship of the individual with a Personal, Divine Savior, and all understanding is unimportant except that relationship. I don’t want to pick on Personal Divine Saviors. People who place New Age crystals or Wicca preeminent are just as misguided. No doubt this practice by individuals distorts original meaning, but the effect is to bless the “gut feel” as being the paramount means of decision, whether in personal lives or polity, or choice of television program. The idea of extended preparation, the long study, the careful training is relegated to the Old Way, or extremely exceptional, or to unimportance in the “real world”. In this world, TV series and sports rule.

The notion extends to business as well, even technical fields, such as in many Web-based businesses where the ideal product is one which demands but an incremental change and brings large profits. Sure, it is sensible to pursue these when they arrive. But it is foolish and unrealistic to think most products will be of this kind, in the same manner that Garrison Keillor’s residents of Lake Wobegon believe “… all the women are strong, all the men are good looking, and all the children are above average.” Most products demand cultivation. Most technical products have, historically, demanded investment, development in proprietary circles, and ultimately release. Financial products may be an exception, but I won’t speculate upon the relationship between those and the movement to demand the same of technical companies.

Whether Americans believe it or not, this tendency to magical thinking or “wishful thinking” or “the triumph of hope over evidence” (*) puts them at a big disadvantage compared to people and countries that do not indulge in this. They think, for instance, that their military is better than anyone’s. Perhaps it is, but to the degree it relies upon technological prowess, that is a standard and a capability which is time-wasting. As the United States painfully learned in the 1950s, without a deep commitment to unfettered scientific research (**), such a lead leaves. And if another country captures it, they can counter us with less. We, as a country, used to believe in “military force multipliers.” I’m sure many professional military still do. But as the Ignorant New Champions of the country get to play out their wet dreams, these are very much at risk.

(*) Indeed, as you’ll from this blog’s description, opposing this is the primary purpose of my blog here.

(**) The sciences are both mutually interdependent and simply do not work well if they are directed. Findings in seemingly unrelated fields support and advance findings in others. I work on Internet data professionally, yet I find the biggest source of results and software and helpful work comes from biostatistics and ecology. Science is pretty much fumbling around in the dark, not so much to pursue things which will produce new products, or new drugs, or new technologies — although there’s more of the latter than the former two — as it is doing things to get a maximal return of insight and knowledge from as little investment as possible. This is not easy, and I daresay it doesn’t always work out as expected. Sometimes that’s a great thing.

## Dedicated to Messrs Trump and Pruitt

Gentlemen: With appreciation for your plan to discourage all visitors to the United States. I applaud your determination.

Let’s go back to the 1950s, shall we?

## Is the answer to the democratization of Science doing more Citizen Science?

I have been following, with keen interest, the post and comment thread pertaining to “Democratising science” at the blog I monitor daily, … and Then There’s Physics. I think the core subject being discussed is a little different from my interest, but it’s all the same big ball of thread. I posted a very long, historically-oriented comment there, wondering and somewhat rhetorically asking what has changed in the United States to make its relationship with Science appear so different?

I write this hear to spare ATTP the need to moderating that additional discussion and because, frankly, it belongs here as a major and different new thesis.

I got into Science as an amateur. Sure, I had a big advantage, because my dad was a Professor of Chemistry at a small liberal arts college in New England. That gave me a mindset, somewhat offset by my parents’ fierce conservative Catholic views, and access to resources, such as a computer I could learn to program in FORTRAN while in Sixth Grade. Both the inevitable conflict between Science and conservative Catholicism and the access to computing dominated my life, in its search for values, and in the perspective I’ve had about almost everything.

But there was Astronomy, my first scientific love. It was neat: You could do it on your own, with a telescope, or someone else’s, and cameras, and even binoculars, and what you learned and gathered and saw was limited by your patience, in New England, your tolerance of cold winter nights with clear skies, and the book-learning you did about the sky, the stars, the constellations, the Main Sequence, spherical trigonometry, the Equation of Time, magazines, and from fellow enthusiasts, skywatchers, stories of Tycho Brahe and Johannes Kepler, telescope builders, and the similarly inclined. For those of us who found Mathematics intriguing, there was the inklings and draw of the mysterious Calculus. It was incredibly empowering for a young person, a nerd, to be able to understand these patterns in a Universe, most of which was so far away.

And then, NASA, and the exploration of near Earth space, and the Moon, and Mars, and spacecraft, and the Jet Propulsion Laboratory in Pasadena …. I got reports about Surveyor III, complete with how these experiments were designed, how the arm spaces were mapped for sampling, how resistance and density in the soils of the Moon was measured by monitoring the back-EMF in the robotic arm used to trench on the surface, how non-orthogonal coordinate systems were natural, and not that intimidating.

And now, way off most people’s radar screens, there is this thing called citizen science. It’s this hobbyist science and the kinds of lyceum-oriented science I wrote about in my comment at ATTP, and it is turned into a real thing. That oughtn’t be surprising. Guy Stewart Callendar was a citizen scientist, even if he was a trained steam mechanisms engineer. Facts are, some people want to do science, and are willing to pay for the privilege and training. Some just devote their spare time, skills, and mind. In any case, it is a serious thing, despite some prejudice shown it by some professionals.

Now, I’m a practicing statistician. Professionally I work for Akamai Technologies in Cambridge, MA. My formal training is that of a software engineer (more than simply a title, with Dijkstra and Meyer as heroes), steeped in numerical analysis and quantitative methods, and that of a test engineer, by professional circumstance. That role led me to re-embrace and indulge in Statistics, which eventually became my life. Predominantly, although not entirely self-taught, I have served many clients and, if I were to identify what I do that brings them the most value, I’d say it is rigorous and unflinching integrity in sources and methods, as well as some facility with picking up applicable if new methods, and teaching their use.

However, outside of work, my biggest scientific and technical efforts lie in the support of furthering this citizen science, whether at the Azimuth Project, which, for other that the Azimuth Data Backup effort has been fairly peripheral, or trying to understand the fresh water hydrology of the Town of Sharon, Massachusetts, using time series of precipitation, well levels, water depths, and water flows in a clutch of areas streams. I have been grossly remiss in my pursuit of the latter, both to that project and to myself. It has not been without reason: Struggling to advocate for sensible energy policy in Massachusetts, educate locally on climate risk and disruption, helping to lead others in this direction, arguing for the moral imperative that climate mitigation deeply is.

But I am wrapping things up, and doing Science and Statistics in its support is the only sane thing I can do to respond to the utter craziness of policy erupting like the pus of a breached boil from 1600 Pennsylvania Avenue. To the degree it pertains to my comment at ATTP, this article neatly sums up both, I think, the opportunities and the issues which might impeded democratization as a practical matter. Clearly, assessing and filtering results from the efforts of citizen scientists is valuable and even essential statistical effort and project, and everything I do from the data collected in support of Sharon’s water concerns is intended to further the efficacy of such contributions. But the deliberate and considered evaluation of methods for assessing citizen science inevitably draws attention, as Kosmala, Wiggins, Swanson, and Simmons point out in their article, to the variability and measurable subjectivity of professional scientific assessments, especially in the field. Part of the difficulty is that, for whatever reason, field scientists generally do not see the necessity of calibrating themselves, even if some of these have been done and reported.

Sure, professional science is indispensable, and the results from the hugely interdisciplinary field of Climate Science are indisputable, an “emerging scientific truth,” as Dr Neil deGrasse Tyson refers to them. But here are some observations:

• A lot of Science is best learnt by doing, not merely studying.
• Scientists teaching and working in the field is probably the best symbolic and practical way of breaking down barriers between concepts of Science as Ivory Tower, and Science as relating to Everybody.
• The funding scene is such that, if citizen science can be exploited for scientific gain, everyone wins.
• The prejudice in peer reviewed journals against research based upon data collected from teams of citizen scientists really needs to be revisited and highlighted. Sure, there’s every reason to be skeptical, and Statistics offers ways of assessing that. But don’t flinch if we statisticians ask the same from the professionals.
• A person does not need to believe in something to be skilled in collecting useful and pertinent data. Accordingly, there’s a role for nearly everyone in the scientific enterprise, no matter what their views.
• Science is a Big Tent. In fact, it’s probably the biggest tent there is. Doing it breaks down barriers. Doing it gives perspective. Doing it can be an almost Buddhist exercise.

So, my answer to scientific democratization is doing more citizen science, and encouraging the re-creation of lyceums and popular scientific societies.