Dynamic hurricane season prediction experiment with the ncep cfs
Download
1 / 47

Dynamic Hurricane Season Prediction Experiment with the NCEP CFS - PowerPoint PPT Presentation


  • 102 Views
  • Uploaded on

Dynamic Hurricane Season Prediction Experiment with the NCEP CFS. Jae-Kyung E. Schemm January 21, 2009 COLA CTB Seminar Acknowledgements: Lindsey Long Suru Saha Shrinivas Moorthi. Outline. Description of the CFS experiment Datasets Used IRI Detection and Tracking Method

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Dynamic Hurricane Season Prediction Experiment with the NCEP CFS' - benito


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Dynamic hurricane season prediction experiment with the ncep cfs

Dynamic Hurricane Season Prediction Experiment with the NCEP CFS

Jae-Kyung E. Schemm

January 21, 2009

COLA CTB Seminar

Acknowledgements: Lindsey Long

Suru Saha

Shrinivas Moorthi


Outline
Outline CFS

  • Description of the CFS experiment

  • Datasets Used

  • IRI Detection and Tracking Method

  • Analysis of storm activity statistics

  • Evaluation of CFS performance on environmental variables related to storm activity

  • A look at CFS-based predictions for 2008 season

  • Summary and future plan


Cfs t382 hurricane season experiments
CFS T382 hurricane season experiments CFS

  • One of the FY07/08 CTB internal projects

  • AGCM - 2007 operational NCEP GFS in T382/L64 resolution

    LSM - Noah LSM

    OGCM - GFDL MOM3

    3. All runs initialized with NCEP/DOE R2 and NCEP GODAS.

    Initial conditions at 0Z, Apr. 19, 20, 21 and May 15(FY07)

    for 1981-2007. Forecasts extended to December 1.

    4. For May 15 cases, runs in T62 and T126 resolutions also performed.


Datasets
Datasets CFS

  • CFS hindcasts at T382

    • May 15th Initial Condition

      • Output at every 3 hours

      • 1981-2007, 27 years

    • April 19th, 20th and 21st Initial Condition

      • Output at every 6 hours

      • 1981-2008, 28 years

      • More appropriate ICs for CPC Operational Hurricane Season Outlook

  • Observations from the HURDAT and JTWC Best Track Dataset

    • Tropical depressions and subtropical storms are not included in storm counts.


Tropical cyclone detection method
Tropical Cyclone Detection Method CFS

  • Based on method devised by Camargo and Zebiak (2002) at IRI

  • Detection algorithm uses basin-dependent threshold criteria for three variables

    • Vorticity, xthresh

      xthresh = 2sx

    • 10-m Wind Speed, uthresh

      uthresh = ugl + suugl= wind speed averaged over

      all global basins

    • Vertically integrated temp anomaly, Tthresh

      • Tthresh = sT/2

      • Calculated using only warm-core systems


Table of basin thresholds
Table of Basin Thresholds CFS

CFS T382 thresholds for vorticity, surface wind speed, and vertically integrated temperature anomaly for each ocean basin.


Eight conditions must be met for a point to be considered a tropical cyclone

1. 850-hPa relative vorticity > xthresh

2. Maximum 10-m wind speed in a 7x7 box > uthresh

3. SLP is the minimum in the centered 7x7 box

4. Temp anomaly averaged over the 7x7 box and three pressure levels (300, 500, & 700 mb) > Tthresh

5. Temperature anomaly averaged over the 7x7 box is positive at all levels (300, 500, & 700 mb) *

6. Temperature anomaly averaged over the 7x7 box at 300mb > 850mb *

7. Wind speed averaged over the 7x7 box at 850mb > 300mb

8. The storm must last for at least 6 hours.

* Criteria 5 & 6 define a warm core system.


Storm tracking
Storm Tracking tropical cyclone

  • Once a point is designated as a tropical cyclone, the cyclone is tracked forward and backward in time to create a full storm track.

  • The maximum vorticity in a 5x5 grid around the cyclone is found and a new 3x3 box is formed around it.

  • At the next time step, if the maximum vorticity in this new box is greater than 3.5 x 10-5 s-1, the procedure is repeated.

  • This point has become part of the storm track.

  • If two storm tracks are the same, they are considered the same cyclone and counted as one.


Four nh ocean basins
Four NH Ocean Basins tropical cyclone


Examples of storm tracks for 4 nh basins

Atlantic tropical cyclone

Eastern North Pacific

Western North Pacific

North Indian

Examples of Storm Tracks for 4 NH Basins


Atlantic tropical cyclone

Basin

Atlantic Tropical Storms


Eastern tropical cyclone

Pacific

Basin

Eastern Pacific Tropical Storms


Western tropical cyclone

Pacific

Basin

Western Pacific Tropical Storms


Atlantic basin correlations
Atlantic Basin Correlations tropical cyclone

Anomalies of Atlantic Storms

N=27 N=13 N=13

Red= Statistically Significant at 0.95


Enp correlations
ENP Correlations tropical cyclone

Anomalies of Eastern North Pacific Storms

N=27 N=13 N=13

Red= Statistically Significant at 0.95


Wnp correlations
WNP Correlations tropical cyclone

Anomalies of Western North Pacific Storms

N=27 N=13 N=13

Red= Statistically Significant at 0.95


Atlantic Basin ACE Index tropical cyclone

% of Normal

N=27 N=13 N=13

Red= Statistically Significant at 0.95


Atl detrended correlations

Correlations tropical cyclone

Total

81-93

94-06

IC=0419

0.24

0.19

0.01

IC=0420

0.34

0.32

0.40

IC=0421

0.25

0.38

0.24

April Ensm

0.35

0.16

0.34

IC=0515

0.22

-0.13

0.42

ATL Detrended Correlations

N=27 N=13 N=13

Red= Statistically Significant at 0.95


Atl detrended step function correlations

Correlations tropical cyclone

Total

81-93

94-06

IC=0419

0.46

0.23

0.15

IC=0420

0.38

0.36

0.45

IC=0421

0.29

0.25

0.10

April Ensm

0.49

0.22

0.30

IC=0515

0.35

0.11

0.49

ATL Detrended, Step Function Correlations

N=27 N=13 N=13

Climatology used for detrending is broken into two 13-year periods, the inactive period of 1981-1993 and the active period 1994-2006

Red= Statistically Significant at 0.95



Jja nino 3 4 sst index
JJA Nino 3.4 SST Index tropical cyclone

Red= Statistically Significant at 0.95


Aso nino 3 4 sst index
ASO Nino 3.4 SST Index tropical cyclone

Red= Statistically Significant at 0.95


Jja atlantic mdr sst index
JJA Atlantic MDR SST Index tropical cyclone

Red= Statistically Significant at 0.95


Aso atlantic mdr sst index
ASO Atlantic MDR SST Index tropical cyclone

Red= Statistically Significant at 0.95


Jja atlantic mdr shear index
JJA Atlantic MDR Shear Index tropical cyclone

Wind Shear:

U200 – U850

Red= Statistically Significant at 0.95


Aso atlantic mdr shear index
ASO Atlantic MDR Shear Index tropical cyclone

Wind Shear:

U200 – U850

Red= Statistically Significant at 0.95


Tna non local index jun nov
TNA Non-Local Index, Jun-Nov tropical cyclone

[60W-30W; 5N-20N] - [0-360, 0-15N] SSTA

Red= Statistically Significant at 0.95



Atlantic basin prediction for 2008
Atlantic Basin Prediction for 2008 tropical cyclone

  • Two additional runs were made using July 15th and 16th initial conditions for 2008 only

  • Used as a trial run for the CPC Hurricane Outlook Update


Atlantic basin cfs 2008 monthly storm count

2008 tropical cyclone

May

Jun

Jul

Aug

Sep

Oct

Nov

Total

0419

1

1

5

3

2

1

1

14

0421

1

3

3

2

4

2

15

0422

1

3

3

3

1

11

ENSM

1

1.33

3.67

2.33

3

1

0.67

13.33

0715

2

4

3

9

0716

1

4

8

2

1

16

Obs

1

3

4

4

1

16

Atlantic BasinCFS 2008 Monthly Storm Count

3


2008 Atlantic Storm Tracks tropical cyclone

(Courtesy of Unisys)

Large number of storms over the Gulf of Mexico this year



. tropical cycloneSummary

  • CFS in T382 resolution exhibits robust climatological seasonal cycle of tropical cyclone over four NH basins.

  • Warming trend and intensification of hurricane activity in the Atlantic basin captured in the CFS hindcasts.

  • Fair level of skill in predicting interannual variability of seasonal storm activities based on the limited number of forecast runs.

  • Model SST and wind shear bias explain part of less number of TCs in Atlantic and EN Pac. basins, in particular over the Gulf of Mexico.

  • Continue to increase number of ensemble members for better climatology and storm statistics. Hope to provide input for 2009 Hurricane Season Outlook with real time prediction runs.

  • Multi-model ensemble approach for dynamical hurricane season prediction is being explored.


ad