Back to home page

Seminar talks with supplements

Archive of all talks

  • Multi-resolution Models for Large Spatial Datasets
    PDF For a general sciences audience. National Science Foundation, April 2014.
    PDF Statistics Department, Iowa State University, Ames IA, March 2013.
    PDF Shorter and more tutorial talk at AGU, San Francisco, December, 2012.

  • KAUST short course on spatial data, inverse problems, and delaing with large data sets Lectures given at KAUST, Saudi Arabia, March 2014

  • Uncertain Climate, Uncertain Weather
    PDF Statistics Department, University of Toronto, March 2013.
    2013 Year of Statistics Public Lecture Series

  • Ten Lectures on Statistics and Climate PDF
    CMBS Lecture series, University of Washington, Seattle, August, 2012.

  • Regional Climate: Design and Analysis of Computer Experiments? PDF
    AGU Fall Meetings, San Francisco, December, 2010.

  • Beyond the hockey stick: indirect methods of paleoclimate reconstruction PDF
    AGU Fall Meetings, San Francisco, December, 2010.

  • Some friendly talks about climate change and statistics

  • Four Lectures on Statistical methods applied to Climate Science
    These lectures were given at the 41st Winter Conference in Statistics at Storhogna, Vemdalen, Sweden March 7-11, 2010. The focus of these lectures in on the statistical analysis of the output from climate model simulations.

  • Two lectures on the relationship between splines and Kriging.
    Most recently given at the University of British Columbia, CA, October 2010. This material is very similar to the fields short course. Demo from lecture. See Short course CD .

  • Statistical Analysis of Regional Climate Models (PDF) 6.5Mb
    An introduction to global and regional climate models for stats folks and some statistical ideas using functional ANOVA and density estimation.
    Oslo, February 2010.
  • Two lectures on the relationship between splines and Kriging.
    Most recently given at the University of British Columbia, CA, October 2010. This material is very similar to the fields short course. Demo from lecture. See Short course CD .

  • Regional Climate

    A Regional climate model animation from NARCCAP
    An animation ncepjan2000.mp4 (6.4Mb) of one of the NARCCAP regional climate models being forced by the global (and lower resolution) NCEP reanalysis field over the month of January 2000 (courtesy of Stephan Sain). See also NARCCAP for information of the sources of these data and model output.

    The NCEP reanalysis is a gridded data product for the atmosphere that uses a weather forecast model with observations to give a physically balanced estimate of the physical variables of the atmopsphere on a 3-d grid. In this animiation the surface precipitation is indicated for NCEP although the actual variables driving (known as forcing) the region model in the interior are moisture, momentum and energy fluxes. This model particular regional model (ECPC) is unusual for a regional model in that it not only uses the fluxes at the domain boundaries but also nudges its interior values to the NCEP field. The finer resolution and more detailed structure in the regional model is considered to be a more accurate simulation of weather processes such as rainfall. The cliamte predicted by the model is found by simulating a long period of weather and averaging the values over time. A numerical simulation where a regional model is forced by observed weather, such as the NCEP reanalysis, is a test of how well the model can reproduced detailed climate under observed conditions. To determine possible changes in climate for the future the NCEP forcings are replaced by the fields from a global climate system that uses future scenarios of greenhouse emissions and other changes to simulate a different set of set of large scale conditions.

  • A Regional climate model animation from NARCCAP

  • Large Spatial data sets

  • What can statistics tell us about the uncertainty of past climate? (PDF) 5.6Mb
    American Public Health Association, San Diego October 2008
  • The uncertain hockey stick: a statistical reconstruction of past temperatures (PDF) 9Mb
    North Symposium, TAMU, June 2009
    ETH seminar, Zurich, CH, November 2009
    The uncertain hockey stick: a statistical reconstruction of past temperatures (PDF) 9Mb
    North Symposium, TAMU, June 2009
    ETH seminar, Zurich, CH, November 2009

    About the Santa ensemble:
    The Santa images are taken from an article: Jason Salavon (2004). Artist Project: 100 Special Moments, Cabinet 15, pp 77- 81.
    Is part of a series of art projects, 100 Special Moments by Jason Salavon. His completed work is Kids with Santa , a composite Santa image that I understand to be a weighted sum of mean and median ensemble pixel values. I was surprised that Salavon's web page does not explicitly show the ensemble or give the details of his process. The construction, even though it is fairly complicated, is not referenced and I interpret this to mean that the process of construction and the underlying sample of 100 images is not important to enjoying the work. But it does raise a caution about taking my illustration in the talk too literally. It is not clear how Salavon choose the 100 Santa images, what digital preprocessing he might have done to align images, adjust color levels, and other manipulations. So the 100 Santa's may not be the kind of representative and random ensemble one would strive for in a statistical context. The 100 images leading to the santa estimate of the "central tendancy" are reproduced in the article by Salavon in Cabinet Magazine, Issue 15.

  • A framework to understand the asymptotic properties of Kriging and splines (PDF) 2.7Mb
    Korean Statistical Society, Seoul, November 2006
    U Wyoming and U Colorado, November 2008
    Colorado State, November 2010
    Technical Report: (PDF)

  • Robust splines and robust wavelets (PDF) 1.7M
    University Wisconsin NCAR, September 2006
    SEE: The Role of Pseudo Data for Robust Smoothing with Application to Wavelet Regression (In review).

  • The Ensemble Kalman Filter: The Movie (PDF) 3.9M
    University of Florida, January 2007
    University Wisconsin, October 2006
    NCAR Advanced study Program, NCAR November, 2005
    Univ. Washington Statistics, November 2006

    The movie: (Quicktime) 32M (First two plots are ensemble mean and sd fields, remaining 6 plots are the first 6 members. The animation brings in each observation sequentially having sorted by location latitude and updates the ensemble. The result of each update is the conditional distribution of the full ozone fields given the observations brought in so far. The first frame are the ensembles draw from an ozone "summer climatology".) The calculations for a large ensemble approximate those needed to update the conditional multivariate normal distribution but instead of keeping track of the conditional covariances and mean the information is propagated by through the discrete distribution represented by the ensemble. Any mean of covariance is determined by the sample statistics based on the ensemble members. The R code available below makes this calculations explicit.

    Do-it-yourself! To construct the frames for this movie, transfer the files README.txt fun.R setup.R from the directory EKFmovie. Follow the instructions in the README.txt file. These animations may seem complicated but there are really just a few tricks (like everything else I do!). Basically a for loop to write out each frame as a separate jpeg image. A key step is that I use Quicktime on a mac to assemble the image sequence into a quick time movie, surprisingly this is just a few clicks. NOTE: These functions require the R statistical environment and the fields package.

  • Statistics, data assimilation and estimating sources of carbon. MSRI Summer Graduate Workshop on Data Assimilation for the Carbon Cycle, MSRI, Berkeley California. July 17 - 21