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

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

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.

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.

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

Acknowledgment to Hai Lin MJO connection to Canadian surface air temperature: high-impact weather? Lagged winter (DJF) SAT anomaly in Canada for 1979-2004 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.

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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

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

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

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

Floods in Pakistan 12

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

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

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

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 1983-2004 CPTEC Centre for Weather Forecasts and Climate Studies 2-tier (15) T62/L28 1979-2001 ECMWF European Centre for Medium Range Weather Forecasts Coupled (41) T159/L62 1981-2005 Exeter Met Office Hadley Centre Coupled (42) 1.25°x1.85°/L38 1989-2002 Melbourne Australian Bureau of Meteorology Coupled (30) T47/L17 1980-2006 Montreal Meteorological Service of Canada 2-tier (40) T32/T63/T95/2.0°x2.0° (4- model combination) 1969-2004 Seoul Korean Meteorological Agency 2-tier (20) T106/L21 1979-2007 Tokyo Japan Meteorological Agency Coupled (51) T95/L40 1979-2008 Toulouse Météo-France T63/L91 Washington National Centres for Environmental Prediction Coupled (40) T62/L64 1981-2004 Moscow Hydromet Centre of Russia 2-tier (10) 1.1°x1.4°/L28 1979-2003 Pretoria South African Weather Service 2-tier (6) T42/L19 1983-2001 WMO Lead-centres for verification and archiving The 12 WMO-designated GPCs

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

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

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)

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 2010. Showing the individual ensemble members (red); and the subsequent verification (blue) 20 20 20

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

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

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?

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

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

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

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

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 ----

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

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

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