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Improving the Validation and Prediction of Tropical Cyclone Rainfall

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Factors impacting rainfall distributions in landfalling TC's ... Kyle. 35. Hermine. 35. Isabel. 90. Isidore. 55. Irene. 70. Georges. 90. Henri. 30. Hanna. 45. Harvey ... – PowerPoint PPT presentation

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Title: Improving the Validation and Prediction of Tropical Cyclone Rainfall


1
Improving the Validation and Prediction of
Tropical Cyclone Rainfall
Robert Rogers NOAA/AOML/HRD Tim Marchok
NOAA/GFDL Bob Tuleya NCEP/EMC/SAIC
Funded by NOAA Joint Hurricane Testbed
2
Rainfall forecasts from landfalling TCs
standard forecasting tools
  • Kraft rule of thumb
  • numerical model guidance
  • R-CLIPER

standard validation tools
  • bias score
  • equitable threat score
  • pattern correlation

3
Factors impacting rainfall distributions in
landfalling TCs
  • storm track
  • topography
  • interaction with synoptic-scale features
  • storm intensity
  • land-surface boundary

4
Track errors for all Atlantic and U.S.
landfalling cases
5
U.S. Landfalling Cases for Model Evaluation
2004
2003
2002
2001
2000
1999
1998
2004
2003
2002
2001
2000
1999
1998
Bonnie
Bill
Bertha
Allison
Gordon 55
Bret
Bonnie
Bonnie
Bill
Bertha
Allison
Gordon 55
Bret
Bonnie
45
45
50
35
45
100
95
50
35
45
100
95
Charley
Claudette
Edouard
Barry
Helene
Dennis
Charley 40
Charley
Claudette
Edouard
Barry
Helene
Dennis
Charley 40
125
125
75
35
60
65
60
75
35
60
65
60
Frances
Grace
Fay
Gabrielle 60
Floyd
Earl
Frances
Grace
Fay
Gabrielle 60
Floyd
Earl
95
95
35
50
90
70
35
50
90
70
Gaston
Henri
Hanna
Harvey
Frances
Gaston
Henri
Hanna
Harvey
Frances
65
65
30
45
50
45
30
45
50
45
Ivan
Isabel
Isidore
Irene
Georges
Ivan
Isabel
Isidore
Irene
Georges
110
110
90
55
70
90
90
55
70
90
Jeanne
Kyle
Hermine
Jeanne
Kyle
Hermine
105
105
35
35
35
35
Matthew
Lili
Matthew
Lili
40
40
85
85
6
Storms Included in this study
7
Models included in this study
GFDL
Regional 1/2o, 1/6o
(2-nest) 42 levels
2003 version
8
Isabel 24-hr rain from 12 UTC 18 to 12 UTC 19
September 2003 (12 UTC 17 forecasts)
Stage IV
9
Parameters describing skill of TC QPF forecasts
  • Pattern
  • Volume
  • Extreme amounts
  • Sensitivity to track errors

10
Matrix of TC QPF Metrics
11
Pattern
12
Pattern comparisons for U.S. landfalling storms
Equitable Threat Score
13
Volume
14
Distributions of rain flux in bands surrounding
storm track
     
 
 
15
Distributions of model rain flux in bands
surrounding forecasted storm track
16
Extreme amounts
17
Top 5 of rain flux comparisons
18
Sensitivity to track error
19
Example of grid-shifting of rain field
Lili Stage IV
r increased from 0.36 (unshifted) to 0.85
(shifted)
20
ETS improvements due to grid shifting
21
Summary comparison for all models
22
Summary comparison for all models (cont.)
23
Future work
  • finish development of a set of metrics that
    synthesizes various aspects of TC QPF
  • determine way of picking out other contributors
    to rainfall variability other than track (e.g.,
    topography) in validation scheme
  • develop parametric rainfall model that accounts
    for vertical shear validate this model using
    same metrics
  • add other sources of variability to new
    parametric model (e.g., topography, synoptic
    environment)

24
New forecasting tools for TC rainfall
25
Example of footprint Hurricane Ivan
a) Wavenumber 0
b) Wavenumber 1,2
mm h-1
mm h-1
06 UTC 09/23/2004
The Footprint is stamped on a lon/lat grid
every 15 minutes, providing a storm total
accumulation
26
Impact of shear on accumulated rain
Only Wave numbers 1,2 included
(inches)
27
Impact of shear on total accumulated rain
Ivan R-CLIPER run including shear
Ivan R-CLIPER control run
(inches)
(inches)
28
QPF Equitable Threat Score
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