Statistics and Climate

Literature Cited

1. Åberg S, Guttorp P. 2008. Distribution of the maximum in air pollution fields. Environmetrics 19:183–208 [Google Scholar]
2. Alpert P, Osetinsky I, Ziv B, Shafir H. 2004. A new seasons definition based on classified daily synoptic systems: an example for the eastern Mediterranean. Int. J. Climatol. 24:1013–21 [Google Scholar]
3. Bachmann D, Dette H. 2005. A note on the Bickel-Rosenblatt test in autoregressive time series. Stat. Probab. Lett. 74:221–34 [Google Scholar]
4. Cierco-Aroylle C, Croquette A, Delmas C. 2003. Computing the distribution of the maximum of Gaussian random processes. Methodol. Comput. Appl. Probab. 5:427–38 [Google Scholar]
5. Craigmile PF, Guttorp P. 2011. Space-time modeling of trends in temperature data. J. Time Ser. Anal. 32:378–95 [Google Scholar]
6. Dehling H, Durieu O, Volny D. 2009. New techniques for empirical processes of dependent data. Stoch. Process. Appl. 119:3699–718 [Google Scholar]
7. Doksum KA. 1974. Empirical probability plots and statistical inference for nonlinear models in the two-sample case. Ann. Stat. 2:267–77 [Google Scholar]
8. Doksum KA, Sievers GL. 1976. Plotting with confidence: graphical comparisons of two populations. Biometrika 63:421–34 [Google Scholar]
9. Field CB, Barros V, Stocker TF, Qin D. 2012. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation Cambridge, UK: Cambridge Univ. Press
10. Foster G, Rahmstorf S. 2011. Global temperature evolution 1979–2010. Environ. Res. Lett. 6:044022 [Google Scholar]
11. Gent PR, Danabasoglu G, Donner LJ, Holland MM, Hunke EC. et al. 2011. The Community Climate System Model version 4. J. Clim. 24:4973–91 [Google Scholar]
12. Gordon C, Cooper C, Senior CA, Banks H, Gregory JM. et al. 2000. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim. Dyn. 16:147–68 [Google Scholar]
13. Guttorp P. 2011. The role of statisticians in international science policy. Environmetrics 22:817–25 [Google Scholar]
14. Guttorp P, Kim TY. 2013. Uncertainty in ranking the hottest years of US surface temperatures. J. Clim. 26:6323–28 [Google Scholar]
15. Hansen J, Ruedy R, Sato M, Lo K. 2010. Global surface temperature change. Rev. Geophys. 48:RG4004 [Google Scholar]
16. Li B, Nychka DW, Ammann CM. 2010. The value of multi-proxy reconstruction of past climate (with discussions and rejoinder). J. Am. Stat. Assoc. 105:883–911 [Google Scholar]
17. Lindgren F, Rue H, Lindström J. 2011. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. J. R. Stat. Soc. B 73:423–98 [Google Scholar]
18. Lund R, Wang XL, Lu Q, Reeves J, Gallagher C, Feng Y. 2007. Changepoint detection in periodic and autocorrelated time series. J. Clim. 20:5178–90 [Google Scholar]
19. Ma Y, Guttorp P. 2013. Estimating daily mean temperature from synoptic climate observations. Int. J. Climatol. 33:1264–69 [Google Scholar]
20. Mote P, Petersen A, Reeder S, Shipman H, Binder LW. 2008. Sea level rise in the coastal waters of Washington State Tech. Rep., Univ. Wash. Clim. Impacts Group, Seattle, WA
21. Ould Haye M, Philippe A. 2011. Marginal density estimation for linear processes with cyclical long memory. Stat. Probab. Lett. 81:1354–64 [Google Scholar]
22. Peixoto JP, Oort AH. 1992. Physics of Climate New York: Am. Inst. Phys.
23. Philipp W, Pinzur L. 1980. Almost sure approximation theorems for the multivariate empirical process. Z. Wahrscheinlichkeitstheorie Verwandte Geb. 54:1–13 [Google Scholar]
24. Rohde R, Muller R, Jacobsen R, Perlmutter S, Rosenfeld A. et al. 2013. Berkeley Earth temperature averaging process. Geoinform. Geostat. Overv. 1:2 [Google Scholar]
25. Rougier J, Goldstein M. 2014. Climate simulators and climate projections. Annu. Rev. Stat. Appl. 1103–23
26. Rue H, Martino S, Chopin N. 2009. Approximate Bayesian inference for latent Gaussian models using integrated nested Laplace approximations (with discussion). J. R. Stat. Soc. B 71:319–92 [Google Scholar]
27. Rüschendorf L. 1974. On the empirical process of multivariate, dependent random variables. J. Multivar. Anal. 4:469–78 [Google Scholar]
28. Sain S, Nychka D, Mearns L. 2011. Functional ANOVA and regional climate experiments: a statistical analysis of dynamic downscaling. Environmetrics 22:700–11 [Google Scholar]
29. Sampson PD, Guttorp P. 1992. Nonparametric estimation of nonstationary spatial covariance structure. J. Am. Stat. Assoc. 87:108–19 [Google Scholar]
30. Shen SSP, Lee SK, Lawrimore J. 2012. Uncertainties, trends, and hottest and coldest years of U.S. surface air temperature since 1895: an update based on the USHCN V2 TOB data. J. Clim. 25:4185–203 [Google Scholar]
31. Shorack G. 1973. Convergence of reduced empirical and quantile processes with application to functions of order statistics in the non-i.i.d. case. Ann. Stat. 1:146–52 [Google Scholar]
32. Smith RL. 1993. Long-range dependence and global warming. Statistics for the Environment V Barnett, F Turkman 141–61 Chichester, UK: Wiley [Google Scholar]
33. Solomon S, Qin D, Manning M, Chen Z, Marquis M. et al. eds 2007. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge, UK: Cambridge Univ. Press
34. Taqqu MS. 2011. The Rosenblatt process. Selected Works of Murray Rosenblatt RA Davis, K-S Lii, DN Politis 29–45 New York: Springer [Google Scholar]
35. Taylor KE, Stouffer RJ, Meehl GA. 2012. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93:485–98 [Google Scholar]
36. Tebaldi C, Strauss BH, Zervas CE. 2012. Modelling sea level rise impacts on storm surges along US coasts. Environ. Res. Lett. 7:014032 [Google Scholar]
37. Thompson WC, Schumann EL. 1987. Interpretation of statistical evidence in criminal trials: the prosecutor's fallacy and the defense attorney's fallacy. Law Hum. Behav. 11:167–87 [Google Scholar]
38. Tingley M, Craigmile P, Haran M, Li B, Mannshardt E, Rajaratnam B. 2012. Piecing together the past: statistical insights into paleoclimatic reconstructions. Q. Sci. Rev. 35:1–22 [Google Scholar]
39. Trenberth K. 1983. What are the seasons?. Bull. Am. Meteorol. Soc. 64:1276–82 [Google Scholar]
40. Trewin B. 2010. Exposure, instrumentation, and observing practice effects on land temperature measurements. WIREs Clim. Change 1:490–506 [Google Scholar]
41. Veillette M, Taqqu MS. 2010. A technique for computing the PDFs and CDFs of nonnegative infinitely divisible random variables. J. Appl. Probab. 48:217–37 [Google Scholar]
42. Vermeer M, Rahmstorf S. 2009. Global sea level linked to global temperature. Proc. Natl. Acad. Sci. USA 106:21527–32 [Google Scholar]
43. Wilk MB, Gnanadesikan R. 1968. Probability plotting methods for the analysis of data. Biometrika 55:1–17 [Google Scholar]
44. WMO 2010. Guide to Climatological Practices Geneva, Switz.: World Meteorol. Organ, 3rd ed..