Toward Seasonal Climate Forecasting and Climate Projections

in Future

Akio KITOHMeteorological Research Institute, Tsukuba, Japan

FOCRAII, 6-8 April 2010, Beijing

Contents

• Seasonal Prediction of Tropical Cyclone Occurrences in the JMA/MRI System

• New MRI/JMA High-Resolution AGCM

• Stratosphere Effect on Prediction of Arctic Oscillation

ENSO influences worldwide climate even out of the tropical Pacific on seasonal to inter-

annual scales.

Sea Surface Temperature anomaly in November 1997

Accumulated Precipitation Anomalyduring Nov.1997-Apr.1998

from BAMS, 1999, 80, S1-48

from JMA webpage

ENSO is the most successfully predicted large-scale phenomenon on seasonal to inter-

annual scales Observatio

nDec1997 - Feb1998

Prediction from

31 July 1997by

JMA/MRI model

Precipitation

Surface Air Temperature

Sea SurfaceTemperature

JMA/MRI

4-month lead

JMA Seasonal Prediction Systemdeveloped by JMA/MRI

JMA/MRI Coupled Model

• JMA/MRI Unified Atmospheric Model

• 180km Resolution (TL95L40)

• Ocean Model (MRI.COM)• 1.0°by 0.3-1.0° 50-layer

• 1-hour Coupling• Wind-stress, Heat-flux Adjustment

Ocean Initials and Data

• MOVE/MRI.COM• Usui et al. (2006)• 3D-VAR (T,S)

• TAO/TRITON array• Altimeter Data• Argo Float

South Asia Summer Monsoon Index (WYI)(4-month lead: JJA from JAN)

AGCMCGCM

WYI Definition: U850–U200 [0-20N,40-110E]

Blue: ForecastRed: Analysis

ACC: 0.59

Blue: ForecastRed: Analysis

ACC: 0.35

JMA/MRI

East Asia Summer Monsoon Index (DU2)(4-month lead: JJA from JAN)

DU2 Definition ：U850[5-15N,90-130E] - U850[22.5-32.5N,110-140E]

Blue: ForecastRed: Analysis

ACC: 0.58

Blue: ForecastRed: Analysis

ACC: -0.05

CGCM AGCM

JMA/MRI

Seasonal Prediction of Tropical Cyclone Occurrences in the

JMA/MRI System

What is predictable?

Simulated Climatological Distribution of Tropical Simulated Climatological Distribution of Tropical DepressionsDepressions

OBS OBS SimulationSimulation

Nakaegawa 2010

Initial: end of April1979-2006Member: 10

ECMWF Newsletter No. 112 – Summer 2007

PredictionPredictionofofTropicalTropicalCycloneCycloneOccurrencesOccurrences

Takaya et al., 2010, submitted

SE

SE

SW

SW

NE

NE

NW

NW

SW

NE

NW

r=0.74

r=0.46

r=0.34

r=0.03 SE

120E

17N

Takaya et al., 2010, submitted

Dependence of Tropical Cyclone Dependence of Tropical Cyclone Occurrence PredictionOccurrence Prediction

on Regionson Regions

Wang and Chan, 2002

MRI/JMA High-Resolution AGCM

impact of horizontal resolution

Future change in NH blocking frequency (JJA)

The higher horizontal resolution is required to accurately simulateEuro-Atlantic blocking. The Euro-Atlantic blocking frequency is predicted to show a significant decrease in the future.

20km

120km 180km

60kmMatsueda

and Palmer(in progress)

AR4 models

wet

dry

AR4 models predict wet (dry) conditions over north (south)Europe. Robust signals from AR4 models.

MRI AGCM

Much weaker signals at high resolution

Precipitation change over Europe (JJA)

180km(climate)

20km(NWP)

similar

robust

less blocking

Matsueda and Palmer (in progress)

AR4 models

wet

dry

AR4 models predict wet (dry) conditions over north (south)Europe. Robust signals from AR4 models.

MRI AGCM

Much weaker signals at high resolution

Precipitation change over Europe (JJA)

180km(climate)

20km(NWP)

similar

robust

less blocking

Matsueda and Palmer (in progress)

Unreliable?

New MRI/JMA High-Resolution AGCM

A new cumulus scheme impact on inter-annual

performance

Old version in 2007 New version in 2010

Horizontal Res. TL319 (60km) TL319 (60km)

Vertical Res. L60 (top 0.1hPa) L64 (top 0.01hPa)

Time-Step 15 minutes 20 minutes

Cumulus Scheme Prognostic AS Yoshimura Scheme

Cloud Scheme Smith (1990) & Kawai (2004)

Tiedtke (1993)

Radiation Shibata & Uchiyama (1992) JMA Scheme (2004_r1)

Gravity wave drag Iwasaki et al. (1989) Iwasaki et al. (1989)

Upper Treatment Newtonian Relaxation Rayleigh Friction

Ocean Surface JMA-Scheme MRI-Scheme & Skin Ocean

Land Surface SIB0109 SIB0109

PBL Mellor-Yamada Level-2 Mellor-Yamada Level-2

Direct Aerosol Effect

Sulphate Sulphate, Organic & Black Carbon, Salt, Mineral

Indirect Effect None None

Two versions of MRI/JMATwo versions of MRI/JMA AGCMsAGCMs

Old60kmmodel

New60kmmodel

New-OldＴＲＭＭ3A25

GPCP&JRA25Reanalysis

CMAP&JRA25Reanalysis

Asian Monsoon ClimatologyAsian Monsoon Climatology （ＪＪ（ＪＪＡ）Ａ）

Seasonal Progress of Monsoon PrecipitationSeasonal Progress of Monsoon Precipitation

Black + ：　 CMAPBlack 　○：　 GPCPRed ：　 New ModelBlue ：　 Old Model

South Asia(India)

Western North Pacific

East Asia(Japan)

Inter-annual Precipitation Variability (Inter-annual Precipitation Variability ( ＪＪＪＪＡＡ ))

Old60km

New60km

GPCP

ＥＯＦ１

ＥＯＦ２

Inter-annual Precipitation Variability (DJF)Inter-annual Precipitation Variability (DJF)

Old60km

New60km

GPCP

ＥＯＦ１

ＥＯＦ２

( 20-100 day band-pass-filtered precipitation anomaly )

Nov.-Apr.

GPCP1DD

Variance of Intra-Seasonal PrecipitationVariance of Intra-Seasonal Precipitation

Old60km

New60km

May-Oct.

Next JMA/MRI-Coupled GCMNext JMA/MRI-Coupled GCM for Seasonal Forecastfor Seasonal Forecast

  Operational CGCM(Feb 2010) Plan for Next CGCM

AGCM TL95L40

Top at 0.4hPa

Gaussian Grids

TL159L60

Top at 0.1hPa

Reduced Grids

OGCM 75S-75N, 0-360E

1.0°by 0.3-1.0°L50

Longitude-Latitude Grids

Climatological Sea Ice

90S-90N, 0-360E

1.0°by 0.3-0.5°L53

Tri-polar Orthogonal Grids

Sea Ice Model

OceanAssimilation

MOVE/MRI.COM

Usui et al. (2006)

3D-VAR(T,S)

T, S on GTS,

COBE-SST, SSH

vertical EOF modes of T-S coupling

MOVE/MRI.COM

for Tri-polar Orthogonal Grids

+

3D-VAR Sea Ice Assimilation

+

Coupled Ensemble Method

(Breeding)

Stratosphere Effect on Prediction of Arctic Oscillation

Toward further improvement of seasonal

prediction NWP model

Typhoon prediction model

El Niño prediction model

Seasonal prediction model

Climate model

Earth system model

Climate model development (IPCC AR4)

It is necessary to explore other predictability sources in the Earth system

Toward further improvement of seasonal

prediction NWP model

Typhoon prediction model

El Niño prediction model

Seasonal prediction model

Climate model

Earth system model

Improving atmosphere-ocean coupled models will lead to constant improvement of seasonal predictions based on slow-coupled process like ENSO.

On the other hand, high predictability from ENSO seems to be limited within relatively low-latitudes.

Therefore, for more complete seasonal prediction, we need to explore other influential elements that show relatively long-range persistency or predictability in the Earth system that consists of upper and/or polar atmosphere, land, snow and ice, chemical processes besides the low-latitude troposphere.

It is necessary to explore other predictability sources in the Earth system

Xie et al. (1999)

JAPAN Winter Temperature is significantly correlated with Arctic Oscillation besides

ENSO 　　

・　 Atlantic SST anomaly

・　 Snow over Eurasia

・　 Arctic Sea Ice Cover

・　 Stratosphere, Ozone

・　 Volcano Eruption

・　 Global Warming

AO

ENSO

Possible Causes

2010/3/3 平成 21年度異常気象分析検討会

Normalized Surface Air Temperature Normalized Surface Air Temperature AnomalyAnomaly

Dec. 2009

Feb. 2010Quick Report

Jan. 2

010

Originally FromJMA Homepage

Most Negative AO index in 2009/10 WinterMost Negative AO index in 2009/10 Winter

DJF AO Variability （上： ERA40+JRA の Z500-

EOF1)（下： JRA+JCDAS の SLP-EOF

1 ）09/1062/63

68/69 76/77 85/86 00/01

09/10 = -3.1

Z500

Originally FromJMA Homepage

From Science (2001)

Role of Stratosphere on Predictability of 2003/04 WinterRole of Stratosphere on Predictability of 2003/04 Winter

Numerical Experiment Design

1.Initials from JMA Objective Analysis

2.Initial Observed SST Anomaly is Fixed

3.Prognostic Land Surface

4.20-member ensemble using every 6-hour Initials (4 times a day) during five days

Observational Data NCEP/NCAR reanalysis

Climatology 1958-2001

MRI/JMA AGCM

(1) Standard Model : TL95L40, Model-Top 0.4 hPa

(2) No Stratosphere Model : TL95L29, Model-Top 40 hPa

From Kuroda (2008)

06Z27Dec 2003- 00Z1Jan 2004

20-Initials Composite

2-month!

Anomalous zonal-mean zonal wind at 60N Anomalous zonal-mean zonal wind at 60N （（ 2003/2004 2003/2004 WinterWinter ））

Shade : Student’s-t

２：９５％ -significance

４：９９．９％ -significance

６： very-high-significance

NCEPReanalysis

PredictionExperiment

Sudden Stratosphere Warming occursDuring early January

From Kuroda (2008)

AGCM

With

Stratosphere

AGCM

Without

Stratosphere

Role of Stratosphere in PredictionRole of Stratosphere in Prediction

2-month!

From Kuroda (2008)

1. Fixed to the Initially Observed SST Anomaly

2. Prognostic Land Surface

1. Climatological SST

2. Climatological Land Surface

Impact of SST and Land Surface State on Impact of SST and Land Surface State on PredictionPrediction

Forecasted anomalous zonal wind

2-month! From Kuroda (2008)

SUMMARY

• High predictability of tropical cyclones’ occurrences is confirmed in the eastern regions of the northwestern Pacific.

• Horizontal resolution matters.• The new cumulus scheme improves the

inter-annual and intra-seasonal variability of the Asian Monsoon simulation with the AGCM.

• Possibility of two-month lead prediction for negative-phase Arctic Oscillations after Stratosphere Sudden Warming.