SPARC - Stratospheric Network for the Assessment of Predictability (SPARC-SNAP)

SPARC - Stratospheric Network for the Assessment of Predictability

(SPARC-SNAP)

SPARC-SNAP TeamOm P Tripathi, Andrew Charlton-Perez, Greg Roff, Mark

Baldwin, Martin Charron, Stephen Eckermann, Edwin Gerber, David Jackson, Yuhji Kuroda, Andrea Lang, Ryo Mizuta,

Michael Sigmond, Seok-Woo Son

Important Potential sources of sub-seasonal (15-60 days) predictability

(S2S Implementation plan)

1. Madden Julian Oscillation (MJO)2. Stratospheric conditions3. Land/Ice/Snow initial condition4. Sea-surface temperature

Important Potential sources of sub-seasonal (15-60 days) predictability

(S2S Implementation plan)

1. Madden Julian Oscillation (MJO)2. Stratospheric initial condition3. Land/Ice/Snow initial condition4. Sea-surface temperature

Processes that impact sub-seasonal skill are not well understoodPredictable skill might be higher in some Window of OpportunityRecognising these window of opportunity is still unclear

Stratospheric Impact at sub-seasonal scale• S2S recognise that the importance of the stratosphere

has not been fully assessed• Case studies has shown that the stratosphere influence

on the extra-tropics• Stratosphere impact NAO and SAM during extreme

vortex events such as SSW• UK Met Office already runs with well resolved

stratosphere and uses Window of Opportunity to re-run the sub-seasonal forecast

• For example Met Office predicted SSW 2013 15 days in advance and corrected (re-run) their sub-seasonal forecast for Europe

S2S and Stratosphere• WCRP-CLIVAR Working group recognise its important

and working on to quantify the improvement in forecast skill via its Stratospheric resolving Historical Forecast Project (SHFP) by employing better resolved stratosphere

• S2S encourages active Collaboration between SHFP and sub-seasonal forecast groups

• SPARC-SNAP’s focus is on the direct contribution at sub-seasonal scale by understanding the stratospheric predictability itself and its contribution to sub-seasonal forecast e.g. exploiting Windows of Opportunity

• S2S plan to archive variables in the stratosphere but the highest level is only 10 hPa

• SPARC-SNAP archives full stratosphere till 1 hPa with models having high vertical resolution in the stratosphere

Stratospheric Network for the Assessment of Predictability

(SNAP)

SNAP Introduction

SPARC – SNAPA network of research and operational communities aims to

answer following fundamental questions:

Are stratosphere-troposphere coupling effects important throughout the winter season or only when major stratospheric dynamical events occur?

How far in advance can major stratospheric dynamical events be predicted and usefully add skill to tropospheric forecasts?

Which stratospheric processes, both resolved and unresolved need to be captured by models to gain optimal stratospheric predictability?

Mark Baldwin University of Exeter, UK

Martin Charron Environment Canada, Canada

Steve Eckermann NRL, USA

Edwin Gerber New York University, USA

Yuhji Kuroda Japan Met Agency, Japan

David Jackson Met Office, UK

Andrea Lang University at Albany, USA

Greg Roff Bureau of Meteorology, Australia

Seok-Woo Son Seoul National University, S Korea

Om Tripathi University of Reading (Co-ordinator)

Andrew Charlton-Perez University of Reading (PI)

Steering Committee

SNAP Activities• A new multi-model experiment to quantify

stratospheric predictability• Stimulate the growth of a community of

researchers interested in stratospheric predictability (workshop, web, newsletters etc).

• A review paper on current understanding of stratospheric predictability (under review)

• A SPARC report and peer-reviewed articles on the findings of the experiment.

SNAP ProtocolCase -15 -10 -5 0 +5

Phase 1: SSW NH 2013

23/12/2012 28/12/2012 02/01/2013 07/01/2013 12/01/2013

Phase 1: Final Warming SH 2012

05/10/2012 10/10/2012 15/10/2012 20/10/2012 25/10/2012

Run Length 15 days

No. of Ensemble members

As many as possible

Phase 0 Current operational forecast for ONE year

Phase 2 TBD (Same as phase I for past cases)

SPARC-SNAP Operational Models and Database

• BADC is hosting SNAP experimental data• Data is accessible on request at

http://badc.nerc.ac.uk/help/jasmin_workspaces.html• For info about SPARC-SNAP activity and data access:

http://www.met.reading.ac.uk/~pn904784/snap/

• Environmental Canada (EC), CANADA• Met Office, UK• Meteorological Research Institute (MRI), JAPAN• Naval Research Laboratory, USA (NAVGEM)• Bureau of Meteorology, Australia (CAWCR)• Korea Meteorological Administration (KMA), Korea• Korea Air Force operational model, Korea Polar Research

Institute, Korea (KOPRI)

http://badc.nerc.ac.uk/help/jasmin_workspaces.html

http://www.met.reading.ac.uk/~pn904784/snap/

Stratospheric Sudden Warming

NH SSW of 2012-2013

Time line of how it happened ?

10 hPa Geopotential Height Zonal mean wind (U) at 10 hPa (60 N)

How it happened

22 December vortex was slight off-pole over Northern Russia31 December its size reduced drastically and moved towards pole05 January elongated over Northern Canada to Northern Russia Wind Reversed at 1 hPa07 January broke into two pieces, larger one over Canada and smaller over Russia

CAWCR Predictability

4. ZONAL MEAN ZONAL WIND

How Basic State (vertical wind configuration) differ during the start of vortex weakening in 15 days and 10 days forecast and 15 days forecast failed ?

31 DECEMBER

ERAI

08 days Forecast:23 Dec


01 JANUARY

ERAI



02 JANUARY

ERAI



03 JANUARY

ERAI



04 JANUARY

ERAI



05 JANUARY

ERAI



06 JANUARY

ERAI



CAWCR Predictability

Stratosphere and Troposphere predictability

How tropospheric forecast of 500 hPa polar cap (60-90 N) Mean Geopotential height differ in 15 day forecast and other forecasts ?

U at 10hPa 60 N

Polar cap Geopotential Height at 500 hPa

23 DECEMBER

U at 10hPa 60 N


-15 days Forecast: Strong ensemble spread in one side for tropospheric forecast after about 4 days

INITIAL PHASE - 1

23 DECEMBER

U at 10hPa 60 N


-15 days Forecast: Strong ensemble spread in one side for tropospheric forecast after about 4 days Ensemble mean tropospheric forecast lost track after 4 days

INITIAL PHASE - 1

28 DECEMBER

U at 10hPa 60 N


-10 days Forecast: Ensemble spread for tropospheric forecast lies both side

INITIAL PHASE - 2

28 DECEMBER

U at 10hPa 60 N


-10 days Forecast: Ensemble spread for tropospheric forecast lies both side AND Ensemble mean tropospheric predictability is more skilful than 15 days forecast

INITIAL PHASE - 2

02 JANUARY

U at 10hPa 60 N


-5 days Forecast: Here also spread is both sided particularly after 5 days in comparison to 15 days forecast

SSW PHASE -1

02 JANUARY

U at 10hPa 60 N


-5 days Forecast: Here also spread is both sided particularly after 5 days in comparison to 15 days forecast AND ensemble mean better represents the tropospheric state

SSW PHASE -1

07 JANUARY

U at 10hPa 60 N


0 days Forecast: Spread is similar to the 10 days and 5 days forecast

SSW PHASE -2

07 JANUARY

U at 10hPa 60 N


0 days Forecast: Spread is similar to the 10 days and 5 days forecast AND tropospheric predictability has similar skill to the last two

SSW PHASE -2

12 JANUARY

U at 10hPa 60 N


+5 days Forecast: Similar spread here

RECOVERY PHASE

12 JANUARY

U at 10hPa 60 N


+5 days Forecast: Similar spread here AND similar tropospheric skill for up to 12 days

RECOVERY PHASE

Models Comparison

1. CAWCR - 24 member ensemble mean

2. JMA - 51 member ensemble mean

3. Korea Polar Research Institute (KOPRI) – GRIMs_V3.2 -3 member (single run initialized by NOAA GDAS1 with model top at 3 hPa on the day, one day before, and one day after)

CAWCR JMA KOPRI

Initial and Boundary condition

APS1 ACCESS-G system, assimilation using observational satellite data, NCEP 1/12 sea ice analysis, fixed SST and sea ice

ERAI + perturbations using BGM cycle, SST anomaly (fix)

NOAA gdas1 analysis

Gravity wave

OGWD scheme and spectral GWD scheme

OGWD SchemeNo Non-OGWD

Resolution N216L70 about 60km horizontal resolution

T159L60 (top at 0.1 hPa), about 110 km

T62L28 (model top at 3hPa)

Summary – S2S and SNAPSNAP is a network to understand stratospheric predictability and its impact on tropospheric forecast may be able to contribute in the S2S RESEARCH ISSUES SNAP Researchers can use S2S archived data to complement the SNAP experimental data to further the understanding of the key processesMany of the S2S models are also part of SNAP making it easier for attribution studies.Research communities are welcome to participate in the Stratospheric Predictability StudySNAP group are keen in the Active and Engaged collaboration with S2S

SummarySNAP aims to look for stratospheric predictability and its impact on tropospheric forecastFirst results of SNAP activities are presented10 day forecast from Australian Operational forecast model has shown a reasonably good predictive skill15 day forecast, however, failed to predict the SSWThe reason appears to be the lack of wave amplification during pre-stage of SSW in 15 day forecast Once the Stratospheric Sudden Warming happens the model has shown to have very good predictive skill up to 15 days during recovery phaseIt appears that when model fails to predict the stratosphere in case of the forecast run of 23 December, the tropospheric predictive skill is poorestFore other forecasts, when the model was able to predict the stratosphere well the tropospheric forecast appeared more skilfulCAWCR appears to have slightly more skill in SSW prediction You are welcome to participate in the Stratospheric Predictability StudyActive and Engaged collaboration with S2S communities

THANK YOU

QUESTIONS ?

SPARC - Stratospheric Network for the Assessment of Predictability (SPARC-SNAP)

Documents

Transcript of SPARC - Stratospheric Network for the Assessment of Predictability (SPARC-SNAP)