Since 2006, in between promoting numeracy in education, and examples of simple statistics using topical issues from the theory of Anthropogenic Global Warming (AGW) to illustrate points, I asked the question “Have these models been validated?”, in blog posts and occasionally submissions to journals. This post summarizes these efforts.
CommentsThe rumbling Alaskan volcano Redoubt has exploded producing a stratosphere-reaching plume in excess of 60,000 ft (17 km). An eruption is termed ‘ultraplinian’ if its ejecta reaches the stratosphere, about 10km in height. Dust and gases in the stratosphere are known to depress the global temperature for up to a few years after the eruption. The extent of cooling depends on the amount and type of material, the size and duration of ultraplinian eruption, and the latitude (high latitude eruptions like Redoubt are less effective than lower ones).
The plume could be seen easily on infrared here (top center of first radar).
A number of familiar tests, often used to evaluate the performance of models: R2 correlation, Nash-Sutcliffe efficiency and similarity of trends and return period, were reported here, noting not much evidence of skill in the DECR models compared with observations at any of these. I also said what a better treatment might entail but left that for another time:
CommentsSteve McIntyre, always gracious in his acknowledgments, mentioned my note in the Australian Institute of Geologists newsletter (AIG News No 83 Mar 2006 pp14) in a post yesterday “The Full Network“. Read the rest of this entry…
CommentsHow many narcissists does it take to change a light bulb?
Just one — but he has to wait for the whole world to revolve around him.
Here is a summary of the chapters in my upcoming book Niche Modeling to be published by CRC Press. Many of the topics have been introduced as posts on the blog. My deepest thanks to everyone who has commented and so helped in the refinement of ideas, and particularly in providing motivation and focus.
Writing a book is a huge task, much of it a slog, and its not over yet. But I hope to get it to the publishers so it will be available at the end of this year. Here is the dustjacket blurb:
Through theory, applications, and examples of inferences, this book shows how to conduct and evaluate ecological niche modeling (ENM) projects in any area of application. It features a series of theoretical and practical exercises in developing and evaluating ecological niche models using a range of software supplied on an accompanying CD. These cover geographic information systems, multivariate modeling, artificial intelligence methods, data handling, and information infrastructure. The author then features applications of predictive modeling methods with reference to valid inference from assumptions. This is a seminal reference for ecologists as well as a superb hands-on text for students.
Functions: This chapter summarizes major types, operations and relationships encountered in the book and in niche modeling. This and the following two chapters could be treated as a tutorial in the R. For example, the main functions for representing the inverted ‘U’ shape characteristic of a niche — step, Gaussian, quadratic and ramp functions – are illustrated in both graphical from and R code. The chapeter concludes with the ACF and lag plots, in one or two dimensions.
Data: This chapter demonstrates how to manage simple biodiversity databases using R. By using data frames as tables,
it is possible to replicate the basic spreadsheet and relational database operations with R’s powerful indexing functions.
While a database is necessary for large-scale data management, R can eliminate conversion problems as data is moved between systems.
Spatial:
R and image processing operations can perform many of the
elementary spatial operations necessary for niche modeling.
While these do not replace a GIS, it demonstrates that generalization of arithmetic concepts to images can be implemented simple spatial operations efficiently.
Theory: Set theory helps to identify the basic assumptions
underlying niche modeling, and the relationships and constraints between these
assumptions. The chapter shows the standard definition of the niche as
environmental envelopes is equivalent to a box topology. It is proven that when
extended to infinite dimensions of environmental variables this definition
loses the property of continuity between environmental and geographic spaces.
Using the product topology for niches would retain this property.
Finally, one journalist has the message right: Duane Freese in his article — “Hockey Stick Shortened?” — at TechCentralStation reports on the National Academy of Sciences report “Surface Temperature Reconstructions for the Last 2,000 Years“. Repetition of the consensus view of strong evidence of recent global warming is not newsworthy. Increase in the uncertainty of the Millennial temperature record is. He says:
The most gratifying thing about the National Academy of Science panel report last week into the science behind Michael Mann’s past temperature reconstructions – the iconic “hockey stick” isn’t what the mainstream media have been reporting — the panel’s declaration that the last 25 years of the 20th Century were the warmest in 400 years.
CommentsThe hockey stick, in short, is 600 years shorter than it was before and the uncertainties for previous centuries are larger than Mann gave credence. And when the uncertainty of the paleoclimatogical record increases with time, the uncertainty about human contribution is likewise increased. Why? For a reason noted on page 103 of the report: climate model simulations for future climates are tuned to the paleoclimatogical proxy evidence of past climate change.
Mathematical shapes can affect our lives and the decisions we make.
The
hockey stick graph describing the earths average temperature over the last millennia has been the subject of a controversial debate over reliability of methods of statistical analysis.
The long tail is another new icon, described in a new book, developed in the Blogosphere, by Chris Anderson called “The Long Tail”:
Forget squeezing millions from a few megahits at the top of the charts. The future of entertainment is in the millions of niche markets at the shallow end of the bit stream. Chris Anderson explains all in a book called “The Long Tail”. Follow his continuing coverage of the subject on The Long Tail blog.
As explained in Wikipedia:
CommentsThe long tail is the colloquial name for a long-known feature of statistical distributions (Zipf, Power laws, Pareto distributions and/or general Lévy distributions ). The feature is also known as “heavy tails”, “power-law tails” or “Pareto tails”. Such distributions resemble the accompanying graph.
In these distributions a low frequency or low-amplitude population that gradually “tails off” follows a high frequency or high-amplitude population. In many cases the infrequent or low-amplitude events—the long tail, represented here by the yellow portion of the graph—can cumulatively outnumber or outweigh the initial portion of the graph, such that in aggregate they comprise the majority.
The Australian Institute of Geoscientists News has published online my article “Reconstruction of past climate using series with red noise” on page 14. Many thanks to Louis Hissink the editor for the rapidity of this publication. It is actually a very interesting newsletter with articles on the IPCC, and a summary of the state of the hockey stick (or hokey stick). There are articles on the K-T boundary controversy and how to set up an exploration company.
CommentsIn honor of the National Research Council of the National Academies committee to study “Surface Temperature Reconstructions for the Past 1,000-2,000 Years” meeting at this moment, I offer my own climate reconstruction based on the methods blessed by dendroclimatology. The graph below shows reconstructed temperature anomolies over 2000 years, with the surface temperature measurements from 1850 from CRU as black dots, the individual series in blue and the climate reconstruction in black. I think you can see the similarity to other published reconstructions (see here), particularly the prominent ‘hockey-stick’ shape, the cooler temperatures around the 1500s and the Medieval Warm Period around the 1000s. What data did I use? Completely random sequences. Reconstruction methods from dendroclimatology will generate plausible climate reconstructions even on random numbers!
The major scientific journals are often regarded as the touchstones of scientific truth. However, their reputation has been tarnished with yet another major scientific fraud unfolding over South Korean researcher Hwang Woo-suk’s peer-reviewed and published Stem Cell research. Should the publication of these results be viewed as simple ‘mistakes’, a crime by a deviant individual, or a broader conspiracy aided by lax reviewing and journal oversight? Blogs were apparently instrumental in uncovering the inconsistencies in Hwangs publications. Here I look at peer-censorship in environmental sciences and its role in concealing scientific waste and fraud, and uncover the emerging solutions from pre-print archives and blogs.
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