Metrics for Model Skill Assessment - PowerPoint PPT Presentation

About This Presentation
Title:

Metrics for Model Skill Assessment

Description:

SAB SST climatology. SST. Chlorophyll. Chlorophyll. Summary ... satellite, in situ, 2004, climatology. Amplitude of variability: good ... – PowerPoint PPT presentation

Number of Views:19
Avg rating:3.0/5.0
Slides: 17
Provided by: ccpo
Learn more at: http://www.ccpo.odu.edu
Category:

less

Transcript and Presenter's Notes

Title: Metrics for Model Skill Assessment


1
Metrics for Model Skill Assessment
  • Model Error time series (model-data misfit)
  • ME(i) model - data
  • Total Root-Mean-Square Error RMS_Total
  • RMS_Total2 RMS_Bias2 RMS_Variability2
  • RMS_Bias difference between means
  • RMS_Variability (centered pattern RMS)
  • mean difference of deviations from mean
  • RMS_Variability Correlation, Amplitude --gt
    Taylor diagram
  • Amplitude of deviations
  • Correlation of deviations

2
Taylor Plot Graphical relationship between time
series based on four statistics 1) Overall
Mean Bias 2) Seasonal Variance Standard
Deviation 3) Timing/Phase Correlation
Coefficient 4) Root Mean Square Error Centered
RMS Distance (RMS_V)

3
Taylor Diagram Example
4
(No Transcript)
5
(No Transcript)
6
(No Transcript)
7
new Run 801
old Run 751
8
(No Transcript)
9
Target Diagram as Skill Assessment Tool
RMS_T2 RMS_B2 RMS_V2
SAB SST climatology
model-data misfit variability in data
model-data misfit error in data
10
SST
11
Chlorophyll
12
Chlorophyll
13
Summary
Taylor Target diagrams are two complimentary
ways of assessing model skill - Taylor
Correlation of variability Amplitude
of variability (Bias) - Target
Total RMS Relative bias and
variability components
14
Summary (cont.)
  • SST
  • Correlation 0.9 always
  • satellite, in situ, 2004, climatology
  • Amplitude of variability good
  • especially for satellite 2004 comparisons
  • underestimate in FL, GA
  • overestimate everywhere north of SC
  • Bias low
  • underestimate in SAB in climatology, better
    using 2004
  • RMS_bias RMS_variability
  • MLD
  • Correlation always positive
  • Higher in MAB (.8) than SAB (.5)
  • Higher in outer SAB (gt.6) than inner SAB (lt.4)
  • Amplitude of variability overestimate
    variability
  • Except for MAB Outer shelf
  • Bias generally low

15
Summary (cont.)
  • Surface chlorophyll - much greater challenge!
  • Correlation -0.6 to 0.9 (same for Clim and
    2004)
  • lower off NC, SC, NY
  • Higher off FL, DE, NJ
  • Amplitude of variability so-so (worse for 2004
    in SAB)
  • underestimate in SAB
  • overestimate in MAB
  • Bias large negative bias everywhere
  • underestimate in GA, SC (benthic production?)
  • underestimate on inner MAB shelf
  • RMS_bias gtgt RMS_variability
  • Little correlation between where MLD/SST is
    modeled
  • well (poorly) and where chlorophyll is modeled
    well (poorly)

16
Future Work
  • Use these Taylor/Target diagrams to compare runs
  • With/without tides
  • With/without DOM
  • Plot other quantities
  • kPAR, productivity, oxygen, salinity
  • Examine other regions
  • Gulf of Maine
  • Gulf Stream/Sargasso
  • Use these for the OCRT meeting?
  • Use these for the Oceanography article?
Write a Comment
User Comments (0)
About PowerShow.com