tropical cyclone genesis frequency over the western north pacific simulated in wcrp cmip3 cgcms

University Allied Workshop (July 1-3, 2008 @ Maihama)

Tropical cyclone genesis frequency over the western North Pacific simulated in WC

RP CMIP3 CGCMs

Satoru Yokoi (CCSR, UT)

Yukari N. Takayabu (CCSR, UT)

Johnny C. L. Chan (City U. Hong Kong)


Motivation

• How may tropical cyclone (TC) frequency change in warmer climate?

• Many previous studies reported that global total TC number will decrease.

• But, quantitative, probabilistic, and regional prediction is yet to be achieved.

It seems necessary to adopt multi-model and multi-ensemble approach.

20C

21C

20C

21C

Difference

Sugi et al. (2002, JMSJ) Bengtsson et al. (2007, Tellus)


CGCM output available at PCMDI

• Under CMIP3 (Phase 3 of Climate Model Intercomparison Project)

• Daily-mean 3-D atmospheric variables of current and global warming climate simulations are available at PCMDI (Program for Climate Model Diagnosis & Inter

comparison).

– 12 CGCMs

– Data period: 40 years (current) & 200 years (GW experiment in total).

• Horizontal resolution of the CGCMs is T106 (1.1) at the utmost, and mainly T42 (2.8) or T63 (1.9).

Studies on TC intensity is difficult, but frequency is possible.

At first, we have to check CGCM performance on TCs.


Purpose

• Evaluate CGCMs’ performance in simulating TC gene

sis frequency (TCGF) over the western North Pacific,

with focusing on horizontal distribution and seasonal

march,

• …, and discuss possible reasons for revealed biases f

rom the viewpoint of reproducibility of environmental c

onditions that affect TCGF.


CGCMs and data

• 12 CGCMs that 3-D daily-mean atmosphere data are available at PCMDI.

– 20th century climate simulations (40 years) are analyzed.

– Daily mean u, v, T, and monthly mean u, v, T, H, and SST.

• Data

– JMA (Japan Meteorological Agency) best track data (1977-2006)

– ECMWF 40-years reanalysis (1982-2001)

– NOAA OISST (1982-2001)

BCCR-BCM2.0, CGCM3.1(T63), CNRM-CM3, CSIRO-Mk3.0,

CSIRO-Mk3.5, ECHAM5/MPI-OM, FGOALS-g1.0, GFDL-CM2.0,

GFDL-CM2.1, INGV-SXG, MIROC3.2(hires), MRI-CGCM2.3.2


Definition of TC-like disturbance

(1) 850 local maximum (=TC center) t. (cyclonic vortex)

(2) (T300 at the center)(environmental T300) Tt. (warm core)

(3) Conditions 1 & 2 are satisfied at least 3 time steps.

(4) Genesis point is over the ocean.

(5) At genesis time, maximum wind speed is greater at the 850-hPa level than at the 300-hPa level.

(exclusion of extra-tropical cyclones)

Threshold values (t, Tt) are determined independently for each model.

They are determined in order that meridional distribution of annual TCGF agrees with the best track data.


Annual TCGF

Obs.

(1) (2) (3) (4)

(5) (6) (7) (8)

(9) (A) (B) (C)

Models

Unit: TCG number in 55 box in 10 years


RMSE of annual TCGF

High performance models: 2, 4, 5, 6, A

Moderate : 1, 3, 8, 9, C

Low : 7, B

4

3.5

3

2.5

2

1.5

1

0.5

01 2 3 4 5 6 7 8 9 A B C

High

LowP

erfo

rman

ce


High performance models

• These models reproduce maxima over the South China Sea and east of Philippines, and relatively low TCGF east of 160E.

(a) Model 1

(b) Model 2

(c) Model 3

(d) Model 4

(e) Model 5

2 4 6 8 10 12

Obs.

[(5x5)-1(10yrs)-1]


Seasonal march in TCGF (110-150E)

• General winter-summer contrast is reproduced.

• 4 models overestimate TCGF in early summer (May-June).

• All models underestimate TCGF in mature summer (July-September), especially to the south of 15N.

Model Obs.

Model 1 Model 3 Model 5

Model 4Model 2

July-September

Black: Obs.Color: models

FGA

FGA


3

700

3

pot

2

200850

5.1

8505

50

70

V

1.01

110GP

H

uu

Genesis potential (GP) index

• Proposed by Emanuel & Nolan (2004).

• Calculate using monthly-mean data.

850: absolute vorticity @850hPa

|u850-u200|: vertical wind shear

Vpot: potential intensity (Bister & Emanuel 2002) H700: relative humidity @700hPa

Dynamic component Thermodynamic component

Vorticity term Shear term Humidity termPI term


Seasonal march in GP (110-150E)

• GP pattern represents TCGF quite well.

• Overestimation in May-June and/or underestimation in July-September.

Model Obs.

normalized

Model 1 Model 3 Model 5

Model 4Model 2


Decomposition of GP

• Two dynamic components (AV & SH) are causes of seasonal bias for all of the 5 models.

termObs.

termModelLog10

Overestimate

Underestimate

AV: Vorticity termSH: Shear termPI : Potential intensity termRH: Humidity term

FGA mean

Model 1

Model 2 Model 4

Model 3 Model 5


Monsoon trough latitude

• A majority of TCs are generated over the monsoon trough.• (MJ) Simulated trough is over the FGA, while the observed one is to its south. Overestimation of TCGF.

• (JAS) Simulated trough is located 15-25N, while the observed one is just over the FGA. Underestimation of TCGF (especially to the south of 15N).

May-June July-September

Mod. 3

Obs.

Pale blue tone & white contour: positive 850

Red vector: u850-u200

Black contour: |u850-u200|

8500 (trough)


Seasonal migration of monsoon trough

• The trough migrates northward too fast and reaches too north.

Model 1

Model 2 Model 4

Model 3 Model 5

850 in 120-150E, positive only, tone: observation.


May-June July-SeptemberObs.

Ridge of subtropical high

• Simulated ridge of subtropical high over western Pacific is too north compared with observation.

Mod. 3

Pale blue tone: positive 850

Black contour: SLP

Red line: Observed ridge

Black points: Simulated ridge


Summary

• I evaluated performance of 12 CGCMs in simulating TCGF over the western North Pacific, using 20th-century climate simulations.

• 5 models reproduce annual TCGF distribution realistically.

• Although these 5 models reproduce general winter-summer contrast, they overestimate TCGF in early summer and underestimate it in mature summer.

• Diagnosis of environmental conditions using GP suggests that the biases are due to unrealistic seasonal migration of monsoon trough; it travels northward too fast and reaches too north.

tropical cyclone genesis frequency over the western north pacific simulated in wcrp cmip3 cgcms

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