¥Several methods available
–Annual (or seasonal extremes), r-largest, POT, simple
indices
¥EV distributions can be fitted by moments, l-moments, mle
–Latter also allows inclusion of covariates (e.g.,
time)
¥Should evaluate
–Feasibility
–Stationarity assumption
–Goodness-of-fit, etc
¥Data limitations
–quality, availability, continuity, etc
–suitability for climate model assessment
¥R-largest and POT methods use data more efficiently
–Do need to be more careful about assumptions
–Data may not be readily available for widespread use
¥Formal climate change detection studies on extremes beginning to appear despite
challenges É
¥Also attempting to estimate FAR (Fraction of Attributable Risk) in the case of Òone-ofÓ
events
–How does one pose the question and avoid selection bias?