Dynamic Hurricane Season Prediction Experiment with the NCEP CFS Jae-Kyung E. Schemm January 21,...

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CFS T382 hurricane season experiments 1.One of the FY07/08 CTB internal projects 2.AGCM 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 Forecasts extended to December 1. 4.For May 15 cases, runs in T62 and T126 resolutions also performed.

Transcript of Dynamic Hurricane Season Prediction Experiment with the NCEP CFS Jae-Kyung E. Schemm January 21,...

Dynamic Hurricane Season Prediction Experiment with the NCEP CFS

Jae-Kyung E. Schemm

January 21, 2009COLA CTB Seminar

Acknowledgements: Lindsey Long Suru Saha Shrinivas Moorthi

Outline

• 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

1. One of the FY07/08 CTB internal projects

2. AGCM - 2007 operational NCEP GFS in T382/L64 resolutionLSM - Noah LSMOGCM - 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 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• Based on method devised by Camargo and

Zebiak (2002) at IRI• Detection algorithm uses basin-dependent

threshold criteria for three variables• Vorticity, thresh

thresh = 2

• 10-m Wind Speed, thresh

thresh = gl + gl = wind speed averaged over all global basins

• Vertically integrated temp anomaly, Tthresh

• Tthresh = T/2 • Calculated using only warm-core systems

Table of Basin Thresholds

ATL ENP WNP NI

* 10-5 4.2 3.9 4.1 4.0

3.5 3.4 3.7 3.4

T 0.31 0.32 0.30 0.28

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

1. 850-hPa relative vorticity > thresh

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

3. SLP is the minimum in the centered 7x7 box4. 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.

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

Storm Tracking• 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

Western North Pacific North Indian

Atlantic Eastern North Pacific Examples of Storm Tracks for 4 NH Basins

AtlanticBasin

Atlantic Tropical Storms

EasternPacificBasin

Eastern Pacific Tropical Storms

WesternPacificBasin

Western Pacific Tropical Storms

Atlantic Basin CorrelationsAnomalies of Atlantic Storms

N=27 N=13 N=13Correlations Total 81-93 94-06

IC=0419 0.44 -0.10 0.14

IC=0420 0.33 0.33 0.36

IC=0421 0.35 0.23 0.24

April Ensm 0.49 0.18 0.33

IC=0515 0.35 0.18 0.40

Red = Statistically Significant at 0.95

N=27 N=13 N=13

ENP CorrelationsAnomalies of Eastern North Pacific Storms

Correlations Total 81-93 94-06IC=0419 -0.04 0.14 -0.14

IC=0420 -0.03 -0.13 -0.06

IC=0421 -0.02 -0.18 0.26

April Ensm -0.07 -0.15 -0.08

IC=0515 0.12 -0.01 -0.02

Red = Statistically Significant at 0.95

N=27 N=13 N=13

WNP Correlations

Red = Statistically Significant at 0.95

Anomalies of Western North Pacific Storms

Correlations Total 81-93 94-06IC=0419 0.40 0.30 0.61IC=0420 0.47 0.19 0.69

IC=0421 0.01 0.27 0.01

April Ensm 0.37 0.25 0.62

IC=0515 0.37 -0.02 0.52

N=27 N=13 N=13Correlations Total 81-93 94-06

IC=0419 0.47 0.05 0.23

IC=0420 0.58 0.70 0.15

IC=0421 0.28 0.00 0.48

April Ensm 0.52 0.23 0.38

IC=0515 0.66 0.61 0.69

Atlantic Basin ACE Index

Red = Statistically Significant at 0.95

% o

f Nor

mal

ATL Detrended Correlations

N=27 N=13 N=13

0.42-0.130.22IC=0515

0.340.160.35April Ensm

0.240.380.25IC=0421

0.400.320.34IC=0420

0.010.190.24IC=0419

94-0681-93TotalCorrelations

Red = Statistically Significant at 0.95

ATL Detrended, Step Function Correlations

N=27 N=13 N=13

0.490.110.35IC=0515

0.300.220.49April Ensm

0.100.250.29IC=0421

0.450.360.38IC=0420

0.150.230.46IC=0419

94-0681-93TotalCorrelations

Red = Statistically Significant at 0.95

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

Evaluation of SST and Wind Shear prediction for storm season

JJA Nino 3.4 SST Index

T382 CORIC=0419 0.722IC=0420 0.667IC=0421 0.677

April Ensm 0.707IC=0515 0.872 Red = Statistically Significant at 0.95

ASO Nino 3.4 SST Index

T382 CORIC=0419 0.690IC=0420 0.603IC=0421 0.626

April Ensm 0.676IC=0515 0.878 Red = Statistically Significant at 0.95

JJA Atlantic MDR SST Index

T382 CORIC=0419 0.629IC=0420 0.635IC=0421 0.726

April Ensm 0.691IC=0515 0.781 Red = Statistically Significant at 0.95

ASO Atlantic MDR SST Index

T382 CORIC=0419 0.643IC=0420 0.655IC=0421 0.771

April Ensm 0.744IC=0515 0.742 Red = Statistically Significant at 0.95

JJA Atlantic MDR Shear Index

T382 CORIC=0419 0.435IC=0420 0.539IC=0421 0.657

April Ensm 0.603IC=0515 0.615 Red = Statistically Significant at 0.95

Wind Shear:U200 – U850

ASO Atlantic MDR Shear Index

T382 CORIC=0419 0.466IC=0420 0.394IC=0421 0.474

Apr Ensm 0.502IC=0515 0.481 Red = Statistically Significant at 0.95

Wind Shear:U200 – U850

TNA Non-Local Index, Jun-Nov

T382 TNAIC=0419 0.364

IC=0420 0.542IC=0421 0.685

April Ensm 0.626

Red = Statistically Significant at 0.95

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

T382 ACE Obs/Fcst

IC=0419 0.467/0.632IC=0420 0.537/0.373

IC=0421 0.757/0.449April Ensm 0.662/0.648

Obs 0.699

2008 Atlantic Season Summary

ObsNOAA

OutlookOutlook

Update

CFS-StatMay

CFS-StatUpdate

Named Storm 16 12-16 14-18 9-16 13-16

Hurricane 8 6-9 7-10 5-9 7-10

Major

Hurricane 5 2-5 3-6 2-4 3-5

Atlantic Basin Prediction for 2008

• 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

13.330.67132.333.671.33 1ENSM

1612841071693420715

1614431Obs

111333104221524233104211411235110419

TotalNovOctSepAugJulJunMay2008

Atlantic BasinCFS 2008 Monthly Storm Count

3

(Courtesy of Unisys)

Large number of storms over the Gulf of Mexico this year

2008 Atlantic Storm Tracks

Resemble Bertha and Cristobal

.Summary 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.