university-logo Metrics for assessing ice sheet model performance Jesse Johnson, Douglas Brinkerhoff, Glen Granzow 17 February, 2010 Land Ice Working Group, Paleo Climate Working Group Joint Session (University of Montana) Metrics LIWG/PCWG Joint Session 1 / 13
29
Embed
Metrics for assessing ice sheet model performance · university-logo Model validation Surface Velocity (University of Montana) Metrics LIWG/PCWG Joint Session 3 / 13. university-logo
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
university-logo
Metrics for assessing ice sheet model performance
Jesse Johnson, Douglas Brinkerhoff, Glen Granzow
17 February, 2010Land Ice Working Group, Paleo Climate Working Group Joint
Session
(University of Montana) Metrics LIWG/PCWG Joint Session 1 / 13
university-logo
Outline
1 IntroductionBackgroundChallenges
2 DistributionsPDFs and binningCDFs and maximum likelihoodSensitivity
3 Summary
(University of Montana) Metrics LIWG/PCWG Joint Session 2 / 13
university-logo
Model validationVolume and Area
(University of Montana) Metrics LIWG/PCWG Joint Session 3 / 13
university-logo
Model validationBasal Temperature
(University of Montana) Metrics LIWG/PCWG Joint Session 3 / 13
university-logo
Model validationSurface Velocity
(University of Montana) Metrics LIWG/PCWG Joint Session 3 / 13
university-logo
A brief history of ice sheet modelingThe Purpose
ice sheet inceptionglacial-interglacial cyclesa source for gravity modelsa source of freshwater for ocean modelslocating and dating ice cores
(University of Montana) Metrics LIWG/PCWG Joint Session 4 / 13
university-logo
A brief history of ice sheet modeling“Validation”
“Paucity of suitable test data...”“geological record is often ambiguous...”“Gross comparisons of the overall patterns...”“...look very reasonable”“...but not full exploited yet”
Huybrechts. Numerical modelling of polar ice sheets through time. Glacier Science and Environmental Change, Chapter 80
(2006) pp. 1-12
(University of Montana) Metrics LIWG/PCWG Joint Session 4 / 13
university-logo
Has the situation changed?Rich data sources
(University of Montana) Metrics LIWG/PCWG Joint Session 5 / 13
university-logo
Has the situation changed?Emphasis on rapid changes
Joughin et al. Large fluctuations in speed on Greenland s Jakobshavn Isbr glacier. Nature (2004) vol. 432 pp. 608-610
(University of Montana) Metrics LIWG/PCWG Joint Session 5 / 13
university-logo
Has the situation changed?Emphasis on short term sea level rise
(University of Montana) Metrics LIWG/PCWG Joint Session 5 / 13
university-logo
Can data be aggregated in meaningful ways?Velocity
(University of Montana) Metrics LIWG/PCWG Joint Session 6 / 13
university-logo
Can data be aggregated in meaningful ways?Velocity Differences
(University of Montana) Metrics LIWG/PCWG Joint Session 9 / 13
university-logo
Is this metric sensitive to the right thing?Balance velocity test
Balance Velocity
∂H∂t
= −∇ · uH + a
∂H∂t
= 0
(University of Montana) Metrics LIWG/PCWG Joint Session 10 / 13
university-logo
Is this metric sensitive to the right thing?Balance velocity test
Accumulation field
a = ∇ · uH
Ettema J., M.R. van den Broeke, E. van Meigaard, W.J. van deBerg, J.L. Bamber, J.E. Box, and R.C. Bales (2009), ”Highersurface mass balance of the Greenland ice sheet revealed byhigh-resolution climate modeling”, Geophys. Res. Lett., 36,L12501, doi:10.1029/2009GL038110
(University of Montana) Metrics LIWG/PCWG Joint Session 10 / 13
university-logo
Is this metric sensitive to the right thing?Balance velocity test
∂H∂t field
a− ∂H∂t
= ∇ · uH
Csatho 2009, personal communication
(University of Montana) Metrics LIWG/PCWG Joint Session 10 / 13
university-logo
Is this metric sensitive to the right thing?Balance velocity test
Utilizing the ∂H∂t field
a −∂H
∂t= ∇ · uH
a − γ
„∂H
∂t
«Dyn
− (1 − γ)
„∂H
∂t
«SMB
= ∇ · uH
Csatho 2009, personal communication
(University of Montana) Metrics LIWG/PCWG Joint Session 10 / 13
university-logo
Sensitivity of α to mass balanceUsing balance velocity calculation
(University of Montana) Metrics LIWG/PCWG Joint Session 11 / 13
university-logo
SummaryThe point of this talk
Distributions of observation and model output may provide a usefulmetric for evaluating ISM output because:
They provide a simple aggregation of a large amount of dataPower law distributions have mature statistical tools for evaluationof dataThese metrics appear to be sensitive to changes in mass balance
(University of Montana) Metrics LIWG/PCWG Joint Session 12 / 13
university-logo
Extra SlideBenford’s Law
(University of Montana) Metrics LIWG/PCWG Joint Session 13 / 13