soc 30/09/04 1 problem areas (?) & possible approaches (?) in ocean extremes clive anderson...
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1SOC 30/09/04
Problem Areas (?)
& Possible Approaches (?)
in Ocean Extremes
Clive AndersonUniversity of Sheffield, UK
2SOC 30/09/04
The Overall Problem
Estimate extremes in presence of
• seasonal variability
• possible long-term trend
• possible relation to other climate variables
• dependent observations
on the basis of
• possibly sparse and irregular data
and give
• realistic assessment of uncertainty of result
3SOC 30/09/04
Problem Areas
• Data from multiple sources - how combine? - how reconcile potential conflicts?
• How extreme? - Description, extrapolation, both?
• Satellite data - how use to augment other data? (as above) - how use alone? * intermittency * spatial resolution, spatial dependence * infer average extreme characteristics?
4SOC 30/09/04
tX X X X
transect times
Intermittency problem
a) over-threshold observations unlikely to be storm peaks
b) many storms likely to be missed
5SOC 30/09/04
• Data from numerical models
- reconcile with observations at extremes?
- assimilate observations at extremes?
6SOC 30/09/04
Approaches (?) 1
• Data from multiple sources - combine? via joint likelihoods
- conflicts? Model relationships of
to underlying variable (Hs say) and incorporate
into likelihoods
Generic form for relationship?
7SOC 30/09/04
Approaches (?) 2
• Satellite data - intermittency and spatial resolution
x
Wave heights: NE Pacific
X
8SOC 30/09/04
tX X X X
transect times
Intermittency problem
a) over-threshold observations unlikely to be storm peaks
b) many storms likely to be missed
X
Handled (crudely) by an asymptotically-justified approximation. Technical improvements appear possible.
9SOC 30/09/04
- How to utilize nearby data?
some form of spatio-temporal model needed
Possibilities:
1. ad hoc weighted (log-)likelihood: likelihood contributions from distant data down-weighted.
2. hierarchical model: if
assume Generalized Pareto, conditionally independent, and
a space-time random field
fitting via MCMC, predictions by simulation
10SOC 30/09/04
4. Structural model representing storms (above-threshold obs.)
3. Moving max models (de Heuvels, Smith & Weissman, Zhang)
11SOC 30/09/04
Atlantic Storm, 1st – 9th December 1997: 6-hourly views
12SOC 30/09/04
4. Structural model
- representing tracks, sizes, intensities of storms
as stochastic elements.
cf Cox & Isham, Smith, Coles, de Haan
- fitting via MCMC, predictions by simulation
13SOC 30/09/04
Approaches (?) 3
• Numerical model data - reconcile with/assimilate real data, emphasizing extremes
cf model uncertainty/calibration/assimilation at non-extreme levels (PC/SOC, Sheffield, Durham
approach uses model emulator based on Gaussian Process)
? for extremes would emulator based on max-stable process be appropriate?
model emulator model inadequacyGaussian process?
14SOC 30/09/04
Geosat 10 day ERS-1 & ERS-2 35 day
ERS-1 168 day