1. Sub-seasonal to seasonal prediction David Burridge (THORPEX IPO) and a cast of …….

2. Incheon, South Korea, November 2009
WMO CAS XV Resolution at
Incheon, South Korea, November 2009
Sub-seasonal to Seasonal Prediction – “….the Commission requested the JSCs of the WWRP and the WCRP and also the THORPEX ICSC to set up an appropriate collaborative structure to carry out an international research initiative on sub-seasonal to seasonal forecasting. It recommended that this is closely coordinated with the present existing CBS infrastructure for long-range forecasting (with centres producing long-range forecasts and regional climate centres) and with the future developments in WMO climate service delivery and the Global Framework for Climate Services called for in the High-Level Declaration of WCC-3.” 2

3. Collaboration between the Weather and Climate Communities to Advance Sub-Seasonal to Seasonal Prediction
To achieve progress in long-range prediction, the coordination of research is needed in: multi-model ensemble prediction system, tropical convection, and its two-way interaction with the global circulation, data assimilation and its socioeconomic applications.
Gilbert Brunet, Melvyn Shapiro, Brian Hoskins, Mitch Moncrieff, Randal Dole, George N. Kiladis, Ben Kirtman, Andrew Lorenc, Brian Mills, Rebecca Morss, Saroja Polavarapu, David Rogers, John Schaake and Jagadish Shukla.

4. First Step Workshop “Sub-seasonal to Seasonal Prediction” Met Office, Exeter –1 to 3 December 2010
The main goals of this Workshop were to establish current capabilities in sub-seasonal to seasonal prediction, to identify high-priority research topics and demonstration projects and to develop recommendations for the establishment of an international research project.

5. Operational Prediction Systems
Medium-range weather predictions (~10-15 days)
Monthly or extended-range predictions (~30-45 days)
Seasonal predictions (~12 months)

6. Acknowledgment to Hai Lin
MJO connection to Canadian surface air temperature: high-impact weather?
Lagged winter (DJF) SAT anomaly in Canada for
Significant warm anomaly in central and eastern Canada 1-2 pentads after MJO phase 3
Acknowledgment to Hai Lin
WMO PTC Meeting, 7-9 February 2011, Geneva.

7. 7

8. Social and Economic Utilization of Sub-Seasonal and Seasonal Predictions
A need for closer ties between weather and climate research:
Understanding how information at the weather/climate interface, including uncertainty, connects with decision-making
There is also a great need for much easier access to forecast data by the user community. These need to be available in special user-oriented products. How could we achieve this service?
The post-processing techniques that are needed by many users may require an archive of past forecasts (e.g. for water cycle applications). Some user applications require an archive of re-forecasts from fixed models for periods as long as 20 years or more. 8 8

9. South American Demonstration Project – Celeste Saulo (CIMA)
Improve predictability by understanding summertime precipitation
La Plata Basin –Forecast Demonstration Project
Variability induced by SACZ / MCSs / blocking events /ENSO / SSTs / Soil Moisture
2003 Salado Flood – initial flooding event ~24 days / secondary event ~2.5 months
Outputs – probabilistic predictions of precipitation / documentation of scientific findings / support from numerical modelling centres in Brazil & Argentina for forecasts & leveraging existing systems & collaborations Ongoing research 9

10. South American Demonstration Project – considerations
The predictability of MCSs in continental regions is a global issue
Biomass burning as a consideration within the models - would the inclusion of other environmental parameters be beneficial to improve forecasts?
Inclusion of hydrological modelling to generate flood forecasts
Landslide risk modelling 10

11. South Asian Demonstration Project – Violeta Toma (GIT)
Implemented 15 day ensemble TC forecasting system
Intensity of TCs (Nargis) not fully captured by models
Flood Forecasting in Bangladesh – 3 tiered system
Experimental real-time 1-10 day flood forecasts
Model lead time & accuracy not the only issue with regard to preventing losses
Importance of understanding the user community for forecast dissemination
Communicating uncertainty – what the warnings mean to the user community
Experimental look at Pakistan floods!
3 tiered system = Seasonal (1-6 m) / intraseasonal (15-30 d) / short term (1-15 d)
Communicating uncertainty – uncertainty involved in the warning message rather than the intricacy of the uncertainty in the model
User community – flood forecasting and warning centre / National Level Emergency Response Group / NGOs / District level relief and emergency 11

12. Floods in Pakistan 12

13. South Asian Demonstration Project – considerations
Hydrological and atmospheric coupling – addition of a storm surge component
Importance of communication with users to understand requirements, best methods of dissemination and to encourage understanding and use of probabilistic forecasts for decision making
How do we verify over these timescales
Need to be able to forecast parameters that can directly inform disaster mitigation decision making – that is Tropical Cyclone intensity intensity and landfall probability at a range of timescales 13

14. Societal and Economic - overall considerations
Important to look at areas with skill & that have willing involvement from community & regional centres
Project Areas:
Agriculture
Rainy season onset
Africa
Polar
Eritrea/Somalia/Kenya
Southern Mexico/Central America
South East Asia
enhancing model predictability through better dynamics and assessing model error/limitations
enhancing predictability through user focussed metrics or indices that relate to the decision making process
Will involve
Variable verification techniques
Decision on how much intricacy is required for the end user to make actionable decisions
Uncertainty is more than the meteorology 14

15. WMO Lead-centres for verification and archiving
WMO CBS has designated Global Producing Centres (GPCs) - currently 12 GPCs satisfying designation criteria
Two Lead Centres, facilitating user access to GPC products
Lead Centre for Long-range Forecast Multi-model Ensembles (LC-LRFMME)
Lead Centre for the Standard Verification System for Long-range Forecasts (LC-SVSLRF)
Aim: improve access and usability of global LRF products to aid production of regional/national climate services
RCOF: regional climate outlook forum 15

16. WMO Lead-centres for verification and archiving
GPC
Centre
System Configuration (ensemble size of forecast)
Resolution (atmosphere)
Hindcast period used
Beijing
Beijing Climate Centre
Coupled (48)
T63/L16
CPTEC
Centre for Weather Forecasts and Climate Studies
2-tier (15)
T62/L28
ECMWF
European Centre for Medium Range Weather Forecasts
Coupled (41)
T159/L62
Exeter
Met Office Hadley Centre
Coupled (42)
1.25°x1.85°/L38
Melbourne
Australian Bureau of Meteorology
Coupled (30)
T47/L17
Montreal
Meteorological Service of Canada
2-tier (40)
T32/T63/T95/2.0°x2.0° (4- model combination)
Seoul
Korean Meteorological Agency
2-tier (20)
T106/L21
Tokyo
Japan Meteorological Agency
Coupled (51)
T95/L40
Toulouse
Météo-France
T63/L91
Washington
National Centres for Environmental Prediction
Coupled (40)
T62/L64
Moscow
Hydromet Centre of Russia
2-tier (10)
1.1°x1.4°/L28
Pretoria
South African Weather Service
2-tier (6)
T42/L19
WMO Lead-centres for verification and archiving
The 12 WMO-designated GPCs

17. JJA forecasts (precipitation) Initialized in May
Beijing ECMWF Exeter Melbourne
Montreal Moscow Seoul Tokyo
Toulouse Washington
From WMO Lead Centre
Downloaded on 1st July
TAC 42 Verification 2010 17

18. WMO Lead-centres for verification and archiving
Forecast and verification products are available to RCCs /NMHSs / RCOFs
Lead Centres will play a key role in WMO Global Seasonal Climate Updates (monitoring and outlook) – part of Global Framework for Climate Services (GFCS) vision.
Key plans for the WMO Lead Centres (guided by the Expert Team for Extended and Long-range Forecasts) include:
development of probability forecast products
extend prediction range (to ~6 months)
verification of multi-model products
possible centralisation of the verification process – currently self-verify
Issue of length of hindcast – but also of consistency of choice of the hindcast period across the GPCs
Working well for seasonal, but not really set up for sub-seasonal timescales
Climate updates for WMO provides pull for 6-month forecasts
Common verification needed for current predictions, not just for retrospective projects
Suggestion to follow the “CMIP model” in making all data available (including hindcast data) rather than focusing on a few measures – many ways of looking at the data 18 18

19. EUROSIP multi-model ensemble
Three European models so far:
ECMWF
Met Office
Meteo-France
Germany planning to contribute
NCEP has just become an associate partner
Not yet integrated into system
An evolving system
Real-time since mid-2005
Common operational schedule (products released at 12Z on 15th)
Monthly mean data in ECMWF operational archive (daily from some partners)

20. Seasonal forecast – Nino SST, annual range
25/04/2017
25/04/2017
Seasonal forecast – Nino SST, annual range
EUROSIP forecasts of SST anomalies over the NINO 3.4 region of the tropical Pacific from July 2009, December 2009 and May Showing the individual ensemble members (red); and the subsequent verification (blue) 20 20 20

21. Data bases 2 CHFP (Climate Historical Forecast Project) YOTC
Database of hindcasts from many models
Using best-available models and data for initialization
Being built now – monthly averages, eventually add daily output
Initial states 4 times a year, from ECMWF or NCEP, 7 month runs, 1979-date
Output (high frequency) at 24h intervals
Hosted in Argentina and UK (exact copies, like TIGGE)
Open to anyone, like TIGGE, for research
Focus on specific research issues through subprojects such as GLACE, SHFP, SeaIce HFP
Suggest important to figure out user needs and how to get data to them first!
YOTC
Includes both model and observed data, and field campaign data
Integrated observational data + high resolution global analysis from ECMWF, NCEP and GMAO/NASA
For research into MJO, Monsoons, Easterly waves and cyclones, tropical-extra tropical interaction; diurnal cycle.
Second copy of data at NCAR soon
ECMWF data portal (like TIGGE), 380 registered users 21

22. Stratospheric Influences on the Troposphere
Monthly Variability
Sudden Stratospheric Warming – Rossby Wave Breaking
NAO/AO Response to Stratospheric Forcing
Apparent Downward Propagation
Can we Predict the Warm?
Yes, 8-14 days in advance
S-I Variability
Stratosphere has long memory – QBO
ENSO Tele-connections in the Stratosphere
Modeling the Stratosphere Improves the Surface Tele-connections
Stratospheric Historical Forecast Project (SHFP) 22

23. Forecast System Standardization
Seasonal predictions
More standardization across different operational centres is required
Seasonal forecast systems are run on a daily, weekly, or a monthly basis
Some data exchange (mostly real-time forecast anomalies) are in place via the efforts of the WMO LC-LRFMME
Some coordination via LC-LRFMME, CHFP etc.
Need common verification data sets (e.g., some use GPCP for precipitation, some Xie-Arkin
Optimum period for hindcasts?

24. Collaboration between the Weather and Climate Communities to Advance Sub-seasonal-to-Seasonal Prediction: Research Issues
Seamless weather/climate prediction with Multi-model Ensemble Prediction Systems
Data assimilation for coupled models as a prediction and validation tool for weather and climate research
Utilization of sub-seasonal predictions for social and economic benefits
Significant progress: The multi-scale organisation of tropical convection and its two-way interaction with the global circulation
Sub-seasonal variability modulates the frequency of high-impact weather (e.g. AO, PNA, Atlantic blockings) 24

25. Monthly / sub-seasonal prediction
In principle, all GPCs that run seasonal predictions, also have monthly predictions – but monthly mean products are not sufficient for monthly to sub-seasonal time-scales
Probably not adequate level of standardization across different operational centers
Monthly forecasts run on a daily or weekly basis
Mix of coupled, or atmospheric alone, prediction systems
No data exchange efforts (?) 25 25

26. Operational monthly to sub-seasonal forecasting
The JMA issues operationally, monthly forecasts every week
The Met Office will start testing a monthly forecast system in spring 2011.
The ECMWF carries out operational monthly prediction with plans to extended the range to 45 days
Starting in January 2011, National Centers for Environmental Prediction (NCEP) will also be running a monthly prediction system.
Canadian plans for the monthly forecast system are to base the monthly forecast system on the Canadian global EPS.
In Australia, the Bureau is currently experimenting with a monthly forecast system.
There was a strong consensus that these operational approaches should be coordinated and the feasibility of data exchange should be investigated 26 26

27. JMA: Yuhei Takaya JMA/MRI-CGCM Monthly Forecast System
Seasonal Forecast System
coupler
(w/ flux adjustment)
Climate DAS JRA-25/JCDAS
JMA/MRI-CGCM
JMA GSM
（TL95L40: ~180km）
Ocean model (MRI.COM )
1.0°×(0.3°-1.0°) ×L51
ODAS MOVE/MRI.COM-G
Atmos perturbs
Trop.&Ext. trop BV
Atmos I. C.
Oceanic I. C.
Atmospheric BGM + Lagged Averaging Forecast
Atmos. perturbations
Trop.&Ext.-trop. bred vec
Atmos I. C.
JMA Global Data Assimilation System
AGCM
(JMA-GSM0803C)
TL159L60 (~110km)
JMA Land Surface Analysis
25 members start from Wed
25 members start from Thurs
50 members in total
9 member ensemble every 5 days 27

28. Capabilities in sub-seasonal prediction
Considerable progress in improving medium-range weather forecasts and developing operational seasonal prediction
Forecasting in the intermediate range between medium range and seasonal is difficult as the importance of the initial conditions wanes, and the importance of slower boundary conditions such as sea surface temperature increases but has only a modest influence on the weather and climate, especially away from the tropical regions.
Progress with representing the ENSO but not solved (including its associated tele-connections)
The MJO is an important source of predictability for the extended range and improving it’s representation improves the prediction of ENSO, theIndian Ocean Dipole, the Northern and Southern Annular Modes and the NAO ----

29. Capabilities/improvements - continued
Parametrization of physical processes
Representing tropical convection and the MJO
Representation of blocking
Land-surface conditions
The influence of the stratosphere
Treatment of the upper ocean
Coupled data assimilation
Data bases to support research
TIGGE
CHFP
SHFP
GLACE
YOTC

30. MAIN RECOMMENDATIONS OF THE WORKSHOP
Establishment of an International Research Project:
Based on the outcome of this workshop, it is recommended that a Panel/Project for Sub-seasonal and seasonal prediction research should be established. Panel members should include representatives from WWRP-THORPEX, WCRP, CAS, CBS, CHY and CCl and their relevant programme bodies. The first task for the Panel will be the preparation of an Implementation Plan which is consistent with the outcome of this Workshop - the main emphasis being on sub-seasonal prediction. 30

31. MAIN RECOMMENDATIONS continued
The Implementation Plan should give high priority to:
Sponsorship of a few international research activities …….
The establishment of collaboration and co-ordination between operational centres undertaking sub-seasonal prediction to ensure, where possible, consistency between operational approaches to enable the production of data bases of operational sub-seasonal predictions to support research
Utilization of data collected for the CHFP, TIGGE GLACE and YOTC for research
The establishment of a series of regular Workshops on sub-seasonal prediction
In a separate plan, or as part of the Implementation Plan, the WWRP/SERA Working Group and WCRP should outline plans for a number of regional projects 31